优先权声明priority statement
本公开要求于2021年2月26日提交的第63/154,223号美国临时专利申请和于2021年3月31日提交的第63/168,635号美国临时专利申请的优先权和权益。这些申请的内容在此通过引用整体并入。This disclosure claims priority and benefit from U.S. Provisional Patent Application No. 63/154,223, filed on February 26, 2021, and U.S. Provisional Patent Application No. 63/168,635, filed on March 31, 2021. The contents of these applications are hereby incorporated by reference in their entirety.
技术领域Technical field
本公开总体上涉及用于呼吸治疗装置的接口，并且更具体地涉及一种基于个体用户数据更好地选择面罩的系统。The present disclosure relates generally to interfaces for respiratory therapy devices, and more specifically to a system for better mask selection based on individual user data.
背景技术Background technique
存在一系列呼吸障碍。某些障碍可以通过特定事件来表征，诸如呼吸暂停、低通气和呼吸过度。阻塞性睡眠呼吸暂停(OSA)是一种睡眠呼吸障碍(SDB)形式，其特征在于包括上部气道在睡眠期间的闭塞或阻塞的事件。它起因于睡眠期间异常小的上部气道和肌肉张力在舌、软腭及后口咽壁分区中的正常丧失的组合。该病症导致受到影响的患者停止呼吸，典型地持续30秒至120秒的时间段，有时每晚200次至300次。这常常导致过度日间嗜睡，并且可能导致心血管疾病和脑损伤。该综合征是一种常见障碍，尤其在中年超重男性中常见，但是受到影响的人可能并未意识到这个问题。A range of respiratory disorders exist. Certain disorders can be characterized by specific events, such as apnea, hypopnea, and hyperpnea. Obstructive sleep apnea (OSA) is a form of sleep disordered breathing (SDB) characterized by events involving occlusion or obstruction of the upper airway during sleep. It results from a combination of abnormally small upper airways and normal loss of muscle tone in the tongue, soft palate, and posterior oropharyngeal wall divisions during sleep. The condition causes affected patients to stop breathing, typically for a period of 30 seconds to 120 seconds, sometimes 200 to 300 times per night. This often leads to excessive daytime sleepiness and can lead to cardiovascular disease and brain damage. The syndrome is a common disorder, especially among middle-aged overweight men, but those affected may not be aware of the problem.
其他睡眠相关障碍包括潮式呼吸(CSR)、肥胖换气过度综合征(OHS)和慢性阻塞性肺病(COPD)。COPD涵盖具有某些共同特性的一组下部气道疾病中的任一种。这些疾病包括空气流动阻力增加、呼吸的呼气阶段延长、以及肺的正常弹性丧失。COPD的实例为肺气肿和慢性支气管炎。COPD由慢性吸烟(主要风险因素)、职业暴露、空气污染和遗传因素所引起。Other sleep-related disorders include Cheyne-Stokes breathing (CSR), obesity hyperventilation syndrome (OHS), and chronic obstructive pulmonary disease (COPD). COPD encompasses any of a group of lower airway diseases that share certain characteristics. These disorders include increased resistance to air flow, prolongation of the expiratory phase of breathing, and loss of normal elasticity of the lungs. Examples of COPD are emphysema and chronic bronchitis. COPD is caused by chronic smoking (a major risk factor), occupational exposure, air pollution and genetic factors.
持续气道正压通气(CPAP)疗法已经被用于治疗阻塞性睡眠呼吸暂停(OSA)。持续气道正压通气的应用充当气动夹板，并且可以通过向前并远离后口咽壁推挤软腭和舌来防止上部气道闭塞。Continuous positive airway pressure (CPAP) therapy has been used to treat obstructive sleep apnea (OSA). The application of continuous positive airway pressure acts as a pneumatic splint and can prevent upper airway occlusion by pushing the soft palate and tongue forward and away from the posterior oropharyngeal wall.
无创通气(NIV)通过上部气道向患者提供通气支持，以帮助患者进行完全呼吸和/或通过完成呼吸功中的一些或全部来维持身体内适当的氧水平。通气支持经由用户接口提供。NIV已经被用于治疗CSR、OHS、COPD和胸壁障碍。在一些形式中，可以改善这些疗法的舒适度和有效性。有创通气(IV)为不再能够自己有效呼吸的患者提供通气支持，并且可以使用气切管提供。Non-invasive ventilation (NIV) provides ventilatory support to the patient through the upper airway to help the patient take a complete breath and/or maintain appropriate oxygen levels in the body by completing some or all of the work of breathing. Ventilation support is provided via the user interface. NIV has been used to treat CSR, OHS, COPD, and chest wall disorders. In some forms, the comfort and effectiveness of these therapies can be improved. Invasive ventilation (IV) provides ventilatory support to patients who are no longer able to breathe effectively on their own and can be provided using a tracheostomy tube.
治疗系统(在本文中也被识别为呼吸治疗系统)可以包括呼吸压力治疗装置(RPT装置)、空气回路、加湿器、用户接口和数据管理。患者或用户接口可用于将呼吸装备接合到其佩戴者，例如通过向气道的入口提供空气流。空气流可以经由面罩提供到患者的鼻和/或嘴、经由管提供到患者的嘴，或经由气切管提供到患者的气管。根据待应用的疗法，用户接口可以例如与患者面部的分区形成密封，以便于以与环境压力有足够差异的压力(例如，以相对于环境压力约10cm H2O的正压)递送气体以实现治疗。对于其他形式的疗法，诸如氧递送，用户接口可能不包括足以便于在约10cm H2O的正压下将气体供应递送到气道的密封。通过这种疗法治疗呼吸疾病可以是自愿的，因此，如果患者发现用于提供这种治疗的装置为：不舒适、难以使用、昂贵和/或不美观，则患者可选择不遵从治疗。A therapy system (also identified herein as a respiratory therapy system) may include a respiratory pressure therapy device (RPT device), air circuit, humidifier, user interface, and data management. A patient or user interface may be used to couple the respiratory equipment to its wearer, such as by providing air flow to the entrance of the airway. Air flow may be provided to the patient's nose and/or mouth via a mask, to the patient's mouth via a tube, or to the patient's trachea via a tracheostomy tube. Depending on the therapy to be applied, the user interface may, for example, form a seal with a partition of the patient's face to facilitate delivery of gas at a pressure that is sufficiently different from ambient pressure (eg, at a positive pressure of approximately 10 cm H2O relative to ambient pressure) to effect therapy. For other forms of therapy, such as oxygen delivery, the user interface may not include a seal sufficient to facilitate delivery of a gas supply to the airway at a positive pressure of approximately 10 cm H2O. Treatment of respiratory conditions with this therapy may be voluntary, so patients may choose not to comply with treatment if they find the device used to provide this therapy to be: uncomfortable, difficult to use, expensive, and/or unsightly.
用户接口的设计提出了若干挑战。面部具有复杂的三维形状。鼻的大小和形状在不同个体之间有很大不同。由于头部包括骨、软骨和软组织，面部的不同分区对机械力的响应不同。下颌或下颌骨可以相对于颅骨的其他骨骼移动。整个头部可以在呼吸治疗时间段的进程中移动。The design of user interfaces presents several challenges. The face has a complex three-dimensional shape. The size and shape of the nose varies greatly between individuals. Because the head consists of bone, cartilage, and soft tissue, different regions of the face respond differently to mechanical forces. The lower jaw, or mandible, can move relative to other bones of the skull. The entire head can be moved over the course of the respiratory therapy session.
由于这些挑战，一些面罩面临以下问题中的一个或多个：突兀、不美观、昂贵、不良适配、难以使用以及特别是当佩戴很长一段时间时或者当用户不熟悉系统时不舒适。例如，仅设计用于飞行员的面罩、设计成个人防护装备的一部分的面罩(例如，过滤面罩)、SCUBA面罩，或设计用于施加麻醉剂的面罩对于面罩的原始应用是可以接受的，但是对于长时期(例如数个小时)佩戴，此类面罩却没有理想的那么舒适。这种不舒适可能引发用户对治疗的依从性降低。如果在睡眠期间佩戴面罩，则这更是如此。Due to these challenges, some masks suffer from one or more of the following issues: obtrusive, unsightly, expensive, poorly fitting, difficult to use, and uncomfortable especially when worn for long periods of time or when the user is unfamiliar with the system. For example, a mask designed only for pilot use, a mask designed to be part of personal protective equipment (e.g., a filter mask), a SCUBA mask, or a mask designed to apply anesthetics would be acceptable for the original application of the mask, but would not be suitable for long-term use. Weared for a period of time (e.g. several hours), this type of mask is not as comfortable as ideal. This discomfort may trigger reduced user compliance with treatment. This is especially true if the mask is worn during sleep.
假设用户遵从治疗，则CPAP疗法对治疗某些呼吸障碍非常有效。获得用户接口允许用户参与正压治疗。寻求他们的第一用户接口或新用户接口来替换旧接口的用户通常咨询耐用医疗装备供应商以基于用户面部解剖结构的测量来确定推荐的用户接口尺寸，这通常由耐用医疗装备供应商执行。如果面罩不舒适或难以使用，用户可能不遵从治疗。由于通常推荐用户定期清洗他们的面罩，因此如果面罩难以清洁(例如难以组装或拆卸)，则用户可能无法清洁他们的面罩，并且这可能影响用户依从性。为了使空气压力疗法有效，不仅必须为佩戴面罩的用户提供舒适度，而且必须在面部和面罩之间形成固体密封以使空气泄漏最小化。CPAP therapy is very effective in treating certain breathing disorders, assuming users comply with treatment. Obtaining a user interface allows the user to participate in positive pressure therapy. Users seeking their first user interface or a new user interface to replace an old interface typically consult the durable medical equipment supplier to determine recommended user interface dimensions based on measurements of the user's facial anatomy, which is typically performed by the durable medical equipment supplier. If the mask is uncomfortable or difficult to use, users may not comply with treatment. Because it is generally recommended that users wash their masks regularly, users may not be able to clean their masks if the mask is difficult to clean (e.g., difficult to assemble or disassemble), and this may affect user compliance. For air pressure therapy to be effective, not only must it provide comfort to the user wearing the mask, but a solid seal must be created between the face and mask to minimize air leakage.
如上所述，用户接口可以以各种形式，例如鼻罩或全面部罩/口鼻罩(FFM)或鼻枕罩提供给用户。使用各种维度制造此类用户接口以适应特定用户的解剖特征，以便于提供例如用于提供正压治疗的舒适接口。此类用户接口维度可以定制成对应于特定用户的特定面部解剖结构，或者可以设计为适应具有落入预定义的空间边界或范围内的解剖结构的个体群体。然而，在一些情况下，面罩可以以多种标准尺寸来提供，必须从这些标准尺寸中选择合适的尺寸。As mentioned above, the user interface may be provided to the user in various forms, such as a nasal mask or a full face mask/oronasal mask (FFM) or a nasal pillow mask. Such user interfaces are manufactured using various dimensions to accommodate the anatomical characteristics of a particular user in order to provide a comfortable interface, for example for providing positive pressure therapy. Such user interface dimensions may be customized to correspond to the specific facial anatomy of a particular user, or may be designed to accommodate a population of individuals with anatomy that falls within predefined spatial boundaries or ranges. However, in some cases, face masks may be supplied in multiple standard sizes from which the appropriate size must be selected.
在这点上，为用户制定用户接口的尺寸通常由训练过的个体来执行，诸如耐用医疗装备(DME)供应商或医师。典型地，需要用户接口来开始或继续正压治疗的用户将在适应设施处访问训练过的个体，在适应设施处进行一系列测量以努力从标准尺寸中确定合适的用户接口尺寸。合适的尺寸旨在意指用户接口的某些特征(诸如密封形成结构)的维度的特定组合，其提供足够的舒适度和密封以实现正压治疗。以这种方式制定尺寸不仅劳动密集而且不方便。在忙碌的日程安排中花费时间或者在某些情况下必须行进很远的距离的不便是对接收新用户接口或替换用户接口的许多用户的障碍，并且最终是对接收治疗的障碍。这种不便妨碍了用户接收需要的用户接口并参与正压治疗。然而，选择最合适的尺寸对于治疗质量和依从性是重要的。In this regard, sizing the user interface for the user is typically performed by a trained individual, such as a durable medical equipment (DME) supplier or physician. Typically, a user who requires a user interface to initiate or continue positive pressure therapy will visit a trained individual at an accommodation facility where a series of measurements are taken in an effort to determine an appropriate user interface size from standard sizes. Suitable sizing is intended to mean a specific combination of dimensions of certain features of the user interface, such as seal-forming structures, that provide adequate comfort and sealing to achieve positive pressure therapy. Dimensing in this manner is not only labor intensive but also inconvenient. The inconvenience of spending time in busy schedules or in some cases having to travel great distances is a barrier to many users receiving a new or replacement user interface, and ultimately, a barrier to receiving treatment. This inconvenience prevents users from receiving the required user interface and participating in positive pressure therapy. However, choosing the most appropriate size is important for treatment quality and compliance.
需要一种系统，该系统允许基于选择的面部维度数据对用户接口进行准确的个性化适配。需要一种系统，该系统结合与使用呼吸治疗装置的其他类似用户有关的数据，以进一步选择在使用中提供呼吸治疗的舒适度的接口。还需要选择一种使接口和用户的面部之间的泄漏最小化的接口。What is needed is a system that allows accurate personalized adaptation of a user interface based on selected facial dimensional data. What is needed is a system that combines data regarding other similar users of respiratory therapy devices to further select interfaces that provide respiratory therapy comfort in use. You also need to choose an interface that minimizes leakage between the interface and the user's face.
发明内容Contents of the invention
公开的系统提供了一种制定面罩尺寸的可适应系统，这些面罩与呼吸治疗装置一起使用，以更好地依从个体用户的治疗。该系统收集来自主用户以及呼吸治疗装置使用的面部数据和来自大量用户的其他数据，以帮助为主用户选择最佳面罩。The disclosed system provides an adaptable system for sizing masks for use with respiratory therapy devices to better comply with individual user therapy. The system collects facial data from the primary user as well as respiratory therapy device usage and other data from a large number of users to help select the best mask for the primary user.
一个公开的实例是选择用于呼吸治疗的适合于用户的面部的接口的系统。该系统包括存储用户的面部图像的存储装置。面部轮廓引擎可操作以基于面部图像确定面部特征。一个或多个数据库存储来自用户群体的多个面部特征和对应的多个接口。一个或多个数据库存储由用户群体使用的具有多个对应的接口的呼吸治疗装置的操作数据。选择引擎联接到数据库。选择引擎可操作以基于期望的效果根据存储的操作数据和确定的面部特征从多个对应的接口中为用户选择接口。One disclosed example is a system that selects an interface for respiratory therapy that fits the user's face. The system includes a storage device that stores facial images of a user. The facial profiling engine is operable to determine facial features based on the facial image. One or more databases store multiple facial features from user groups and corresponding multiple interfaces. One or more databases store operational data for respiratory therapy devices having a plurality of corresponding interfaces used by a user community. The selection engine connects to the database. The selection engine is operable to select an interface for the user from a plurality of corresponding interfaces based on a desired effect based on the stored operational data and the determined facial characteristics.
另一公开的实例是一种选择用于呼吸治疗的适合于用户的面部的接口的方法。用户的面部图像存储在存储装置中。基于这些界标来确定面部维度。将来自用户群体和由患者群体使用的对应的多个接口的多个面部特征存储在一个或多个数据库中。由用户群体使用的具有多个对应的接口的呼吸治疗装置的操作数据存储在该一个或多个数据库中。基于期望的效果根据存储的操作数据和确定的面部特征从多个对应的接口中为用户选择接口。Another disclosed example is a method of selecting an interface for respiratory therapy that is suitable for a user's face. The user's facial image is stored in the storage device. Facial dimensions are determined based on these landmarks. Multiple facial features from a user population and corresponding multiple interfaces used by a patient population are stored in one or more databases. Operational data of respiratory therapy devices with corresponding interfaces used by a user community are stored in the one or more databases. An interface is selected for the user from a plurality of corresponding interfaces based on the desired effect based on the stored operational data and the determined facial characteristics.
根据一些实施方式，一种示例方法包括接收与接口在用户的面部上的当前适配性相关联的传感器数据。该接口可联接到呼吸装置。该传感器数据由可与呼吸装置分离的移动装置的一个或多个传感器收集。该方法还包括使用该传感器数据生成面部映射。该面部映射指示用户的面部的一个或多个特征。该方法还包括使用传感器数据和面部映射来识别与当前适配性相关联的特性。该特性指示当前适配性的质量。该特性与面部映射上的特性位置相关联。该方法还包括基于识别的特性和特性位置生成输出反馈。可以生成输出反馈以评估或改善当前适配性。According to some embodiments, an example method includes receiving sensor data associated with a current fit of an interface on a user's face. This interface can be coupled to a breathing device. The sensor data is collected by one or more sensors of the mobile device that is detachable from the breathing device. The method also includes generating a facial map using the sensor data. The facial map indicates one or more features of the user's face. The method also includes using sensor data and facial mapping to identify characteristics associated with current fitness. This property indicates the quality of the current fitness. The feature is associated with the feature location on the face map. The method also includes generating output feedback based on the identified features and feature locations. Output feedback can be generated to evaluate or improve current fitness.
根据一些实施方式，一种示例系统包括电子接口、存储器和控制系统。该电子接口被配置成接收与接口的当前适配性相关联的数据。该存储器存储机器可读指令。该控制系统包括一个或多个处理器，该一个或多个处理器被配置成执行机器可读指令以使用接收的数据生成面部映射，并且基于接收的数据和该面部映射来识别与当前适配性相关联的特性。该控制系统还被配置成基于识别的特性生成输出反馈。可以生成输出反馈以评估或改善当前适配性。According to some implementations, an example system includes an electronic interface, memory, and a control system. The electronic interface is configured to receive data associated with the current suitability of the interface. This memory stores machine-readable instructions. The control system includes one or more processors configured to execute machine-readable instructions to generate a facial map using the received data, and to identify a current fit based on the received data and the facial map. Sex-related properties. The control system is also configured to generate output feedback based on the identified characteristics. Output feedback can be generated to evaluate or improve current fitness.
以上发明内容并不旨在表示本公开的每个实施例或每个方面。相反，前述发明内容仅提供了本文阐述的一些新颖方面和特征的实例。当结合附图和所附权利要求考虑时，从以下用于执行本发明的代表性实施例和模式的详细描述中，本公开的上述特征和优点以及其他特征和优点将显而易见。The above summary is not intended to represent every embodiment or every aspect of the disclosure. Rather, the foregoing summary provides only examples of some of the novel aspects and features set forth herein. The above-described features and advantages of the present disclosure, as well as other features and advantages, will be apparent from the following detailed description of representative embodiments and modes for carrying out the invention, when considered in conjunction with the accompanying drawings and appended claims.
附图说明Description of the drawings
从以下结合附图对示例性实施例的描述中将更好地理解本公开，在附图中：The present disclosure will be better understood from the following description of exemplary embodiments taken in conjunction with the accompanying drawings, in which:
图1示出了一种系统，该系统包括佩戴全面部面罩形式的用户接口的用户，以从示例呼吸压力治疗装置接收PAP疗法；1 illustrates a system that includes a user wearing a user interface in the form of a full-face mask to receive PAP therapy from an example respiratory pressure therapy device;
图2示出了根据本技术的一种形式的具有头戴设备的鼻罩形式的用户接口；2 illustrates a user interface in the form of a nasal mask with a headset in accordance with one form of the present technology;
图3A是具有表面解剖结构的数个特征的面部的正视图；Figure 3A is a front view of a face with several features of surface anatomy;
图3B是具有识别的表面解剖结构的数个特征的头部的侧视图；Figure 3B is a side view of a head with several features of identified surface anatomy;
图3C是具有识别的数个特征的鼻的底视图；Figure 3C is a bottom view of the nose with several features identified;
图4A示出了根据本技术的一种形式的呼吸压力治疗装置；Figure 4A illustrates one form of respiratory pressure therapy device in accordance with the present technology;
图4B是根据本技术的一种形式的呼吸压力治疗装置的气动路径的示意图；4B is a schematic diagram of a pneumatic path of a respiratory pressure therapy device in accordance with one form of the present technology;
图4C是根据本技术的一种形式的呼吸压力治疗装置的电气部件的示意图；4C is a schematic diagram of the electrical components of a respiratory pressure therapy device in accordance with one form of the present technology;
图4D是根据本技术的一种形式的呼吸压力治疗系统的主要数据处理部件的示意图；Figure 4D is a schematic diagram of the primary data processing components of a respiratory pressure therapy system in accordance with one form of the present technology;
图5是声学传感器在向图2中的用户接口供应空气的软管中的布置的框图；Figure 5 is a block diagram of the arrangement of an acoustic sensor in a hose supplying air to the user interface in Figure 2;
图6是用于捕捉面部数据的计算装置的部件的图；Figure 6 is a diagram of components of a computing device for capturing facial data;
图7是用于自动选择患者接口的示例系统的图，该系统包括计算装置；7 is a diagram of an example system for automatically selecting a patient interface, the system including a computing device;
图8A是示例面部扫描，该示例面部扫描示出了不同的界标点以识别用于面罩尺寸制定的面部维度；8A is an example facial scan showing different landmark points to identify facial dimensions for mask sizing;
图8B是图8A中的面部扫描的视图，该视图示出了不同的界标点以识别第一面部测量；Figure 8B is a view of the facial scan of Figure 8A showing different landmark points to identify the first facial measurement;
图8C是图8A中的面部扫描的视图，该视图示出了不同的界标点以识别第二面部测量；Figure 8C is a view of the facial scan in Figure 8A showing different landmark points to identify second facial measurements;
图8D是图8A中的面部扫描的视图，该视图示出了不同的界标点以识别第三面部测量；Figure 8D is a view of the facial scan in Figure 8A showing different landmark points to identify third facial measurements;
图9是考虑到从用户数据库收集的大数据，基于用户输入的扫描和分析为用户选择面罩的过程的流程图；Figure 9 is a flowchart of the process of selecting a mask for a user based on scanning and analysis of user input, taking into account big data collected from the user database;
图10是根据面罩的初始选择以根据与主用户有关的数据调整相关参数的后续评估过程的流程图；Figure 10 is a flow diagram of a subsequent evaluation process based on the initial selection of a mask to adjust relevant parameters based on data related to the primary user;
图11是控制用户装置以收集与用户接口的当前适配性相关联的传感器数据的用户的透视图；11 is a perspective view of a user controlling a user device to collect sensor data associated with current suitability of the user interface;
图12是用于识别与用户接口的当前适配性相关联的热特性的用户装置的用户视图；12 is a user view of a user device for identifying thermal characteristics associated with current suitability of a user interface;
图13是用于识别与用户接口的当前适配性相关联的基于轮廓的特性的用户装置的用户视图；13 is a user view of a user device for identifying contour-based characteristics associated with current suitability of a user interface;
图14是描绘用于评估用户接口跨用户接口转换事件的适配性的过程的流程图；以及14 is a flowchart depicting a process for evaluating the suitability of a user interface across user interface transition events; and
图15是描绘用于评估用户接口的适配性的过程的流程图。Figure 15 is a flowchart depicting a process for evaluating the suitability of a user interface.
本公开容许各种修改和替代形式。在附图中以实例的方式示出了一些代表性实施例，并且将在本文中对其进行详细描述。然而，应当理解，本发明并不旨在限于公开的特定形式。相反，本公开将覆盖落入由所附权利要求限定的本发明的精神和范围内的全部修改、等同物和替代物。The present disclosure is susceptible to various modifications and alternative forms. Some representative embodiments are shown by way of example in the drawings and will be described in detail herein. It should be understood, however, that the invention is not intended to be limited to the particular forms disclosed. On the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.
具体实施方式Detailed ways
本发明可以以许多不同的形式体现。在附图中示出了代表性实施例，并且将在本文中对其进行详细描述。本公开是本公开的原理的实例或说明，并且不旨在将本公开的广泛方面限制于说明的实施例。在此程度上，例如在摘要、发明内容和具体实施方式章节中公开但未在权利要求中明确阐述的要素和限制不应当通过暗示、推断或其他方式单独或共同地并入权利要求中。出于具体实施方式的目的，除非明确否认，否则单数包括复数，反之亦然；并且词语“包括”意指“包括但不限于”。此外，诸如“约”、“几乎”、“基本上”、“大致”等的近似词在本文中可以用于意指例如“为”、“接近”，或“几乎为”，或“在3至5％内”，或“在可接受的制造公差内”，或其任何逻辑组合。The invention can be embodied in many different forms. Representative embodiments are illustrated in the drawings and are described in detail herein. This disclosure is an example or illustration of the principles of the disclosure and is not intended to limit the disclosure in its broad aspects to the illustrated embodiments. To this extent, elements and limitations disclosed, for example, in the Abstract, Summary, and Detailed Description sections but not expressly set forth in the claims shall not be incorporated into the claims, individually or collectively, by implication, inference, or otherwise. For purposes of the Detailed Description, the singular includes the plural and vice versa unless expressly denied; and the word "includes" means "including but not limited to." In addition, approximate words such as "about," "almost," "substantially," "approximately," etc. may be used herein to mean, for example, "for," "nearly," or "nearly for," or "within 3 to within 5%", or "within acceptable manufacturing tolerances", or any logical combination thereof.
本公开涉及一种用于为使用呼吸治疗装置的用户选择最佳接口的系统和方法。该系统从移动装置上的面部扫描应用收集来自用户的个体面部特征数据，并根据扫描的图像生成面部的3D模型。该系统在扫描的图像上精准确定关键界标，以确定不同的面部维度。该系统收集来自多个用户的数据，以基于来自使用不同的面罩的呼吸治疗装置的用户数据和操作数据来学习不同的面罩和成功的呼吸治疗之间的相关性。该系统使用面部维度数据和从多个用户收集的数据，以基于从使用接口和呼吸治疗装置的多个用户收集的数据，与过去的成功匹配相比，为用户选择合适的面罩尺寸和类型。该数据还可用于进一步学习可提供给用户以增加对治疗的依从性/坚持的新见解。因此，该方法将合适的面部扫描方法与界标识别、面罩选择、治疗监测和反馈相结合，以提供有效的用户接口选择。The present disclosure relates to a system and method for selecting an optimal interface for a user using a respiratory therapy device. The system collects individual facial feature data from the user from a facial scanning application on the mobile device and generates a 3D model of the face based on the scanned image. The system accurately identifies key landmarks on scanned images to identify different facial dimensions. The system collects data from multiple users to learn correlations between different masks and successful respiratory therapy based on user data and operational data from respiratory therapy devices using different masks. The system uses facial dimensional data and data collected from multiple users to select the appropriate mask size and type for the user based on data collected from multiple users using the interface and respiratory therapy device compared to past successful matches. This data can also be used to further learn new insights that can be provided to users to increase compliance/adherence to treatment. Therefore, this approach combines suitable facial scanning methods with landmark recognition, mask selection, treatment monitoring and feedback to provide effective user interface selection.
本公开的某些方面和特征涉及评估和改善用户接口(例如，过滤面罩或呼吸治疗装置的用户接口)的适配性。可以利用来自用户装置(例如，便携式用户装置，诸如智能电话，也称为移动计算装置或移动装置)的一个或多个传感器的传感器数据来帮助用户确保可佩戴用户接口(例如，将与呼吸装置一起使用的用户接口)适当地适配于用户面部。传感器可以i)在戴上用户接口之前；ii)在佩戴用户接口的同时；和/或iii)在移除用户接口之后，收集关于用户面部的数据。可以生成面部映射，从而识别用户面部的一个或多个特征。然后可以利用传感器数据和面部映射来识别与用户接口的适配性相关联的特性，这些特征可用于生成输出反馈以评估和/或改善适配性。Certain aspects and features of the present disclosure relate to evaluating and improving the fit of a user interface (eg, a user interface of a filtering mask or respiratory therapy device). Sensor data from one or more sensors of a user device (e.g., a portable user device such as a smartphone, also known as a mobile computing device or mobile device) may be utilized to assist the user in ensuring that a wearable user interface (e.g., will interface with a respiratory device used with the user interface) appropriately adapts to the user's face. The sensor may collect data about the user's face i) before putting on the user interface; ii) while wearing the user interface; and/or iii) after removing the user interface. A facial map can be generated to identify one or more features of a user's face. Sensor data and facial mapping can then be leveraged to identify features associated with the fit of the user interface, which can be used to generate output feedback to evaluate and/or improve fit.
在公开的示例系统的其他实施方式中，该接口是面罩。在另一实施方式中，呼吸治疗装置被配置成提供气道正压通气(PAP)或无创通气(NIV)中的一种或多种。在另一实施方式中，呼吸治疗装置中的至少一个包括音频传感器，以在呼吸治疗装置中的至少一个的操作期间收集音频数据。在另一实施方式中，选择引擎可操作以分析该音频数据，以基于将该音频数据与已知接口的声学特征标记进行匹配来确定呼吸治疗装置中的至少一个的对应的接口的类型。在另一实施方式中，选择引擎基于用户的人口统计数据与存储在一个或多个数据库中的用户群体的人口统计数据的比较来选择接口。在另一实施方式中，操作数据包括流速、电动机速度、和治疗压力中的一者。在另一实施方式中，根据来自包括相机的移动装置的扫描来确定面部图像。在另一实施方式中，该移动装置包括深度传感器。该相机是3D相机。面部特征是从由面部图像导出的网格化表面导出的三维特征。在另一实施方式中，该面部图像是包括界标的二维图像，并且面部特征是从这些界标导出的三维特征。在另一实施方式中，面部图像是多个二维面部图像中的一个。面部特征是从适于匹配面部图像的3D形变模型导出的三维特征。在另一实施方式中，面部图像包括与至少一个面部维度相关的界标。在另一实施方式中，面部维度包括面部高度、鼻宽度、和鼻深度。在另一实施方式中，期望的效果是接口和面部表面之间的密封以防止泄漏。在另一实施方式中，期望的效果是用户对治疗的依从性。在另一实施方式中，该系统包括移动计算装置，该移动计算装置可操作以收集从用户输入的主观数据，并且接口的选择至少部分地基于该主观数据。在另一实施方式中，该系统包括机器学习模块，该机器学习模块可操作以确定与实现期望的效果的接口关联的操作数据的类型。在另一实施方式中，选择的接口包括多种类型的接口中的一种和多种尺寸的接口中的一种。在另一实施方式中，选择引擎基于操作选择的接口接收来自用户的反馈，并且基于不期望的结果，基于期望的效果选择另一接口。在另一实施方式中，不期望的结果是用户对治疗的低依从性、高泄漏、或不令人满意的主观结果数据中的一者。In other embodiments of the disclosed example systems, the interface is a mask. In another embodiment, the respiratory treatment device is configured to provide one or more of positive airway pressure (PAP) or non-invasive ventilation (NIV). In another embodiment, at least one of the respiratory treatment devices includes an audio sensor to collect audio data during operation of at least one of the respiratory treatment devices. In another embodiment, the selection engine is operable to analyze the audio data to determine a corresponding type of interface for at least one of the respiratory treatment devices based on matching the audio data with acoustic signatures of known interfaces. In another embodiment, the selection engine selects the interface based on a comparison of the user's demographic data with the demographic data of the user population stored in one or more databases. In another embodiment, the operational data includes one of flow rate, motor speed, and treatment pressure. In another embodiment, the facial image is determined from scans from a mobile device including a camera. In another embodiment, the mobile device includes a depth sensor. This camera is a 3D camera. Facial features are three-dimensional features derived from meshed surfaces derived from facial images. In another embodiment, the facial image is a two-dimensional image including landmarks, and the facial features are three-dimensional features derived from the landmarks. In another embodiment, the facial image is one of a plurality of two-dimensional facial images. Facial features are three-dimensional features derived from a 3D deformation model adapted to match facial images. In another embodiment, the facial image includes landmarks associated with at least one facial dimension. In another embodiment, facial dimensions include facial height, nasal width, and nasal depth. In another embodiment, the desired effect is a seal between the interface and the facial surface to prevent leakage. In another embodiment, the desired effect is user compliance with treatment. In another embodiment, the system includes a mobile computing device operable to collect subjective data input from a user, and the selection of the interface is based at least in part on the subjective data. In another embodiment, the system includes a machine learning module operable to determine a type of operational data associated with an interface that achieves a desired effect. In another embodiment, the selected interface includes one of multiple types of interfaces and one of multiple sizes of interfaces. In another embodiment, the selection engine receives feedback from the user based on the interface selected by the operation and selects another interface based on the desired effect based on undesirable results. In another embodiment, the undesirable outcome is one of low user compliance with treatment, high leakage, or unsatisfactory subjective outcome data.
在提供合适的适配接口的上述公开的方法的其他实施方式中，该接口是面罩。在另一实施方式中，呼吸治疗装置被配置成提供气道正压通气(PAP)或无创通气(NIV)中的一种或多种。在另一实施方式中，呼吸治疗装置中的至少一个包括音频传感器，以在呼吸治疗装置中的至少一个的操作期间收集音频数据。在另一实施方式中，选择包括分析该音频数据以基于将该音频数据与已知接口的声学特征标记进行匹配来确定呼吸治疗装置中的至少一个的对应的接口的类型。在另一实施方式中，该选择包括将用户的人口统计数据与存储在一个或多个数据库中的用户群体的人口统计数据进行比较。在另一实施方式中，操作数据包括流速、电动机速度和治疗压力中的一者。在另一实施方式中，根据来自包括相机的移动装置的扫描来确定面部图像。在另一实施方式中，该移动装置包括深度传感器。该相机是3D相机，并且面部特征是从由面部图像导出的网格化表面导出的三维特征。在另一实施方式中，该面部图像是包括界标的二维图像，并且面部特征是从这些界标导出的三维特征。在另一实施方式中，面部图像是多个二维面部图像中的一个。这些面部特征是从适于匹配面部图像的3D形变模型导出的三维特征。在另一实施方式中，面部图像包括与至少一个面部维度有关的界标。在另一实施方式中，面部维度包括面部高度、鼻宽度、和鼻深度。在另一实施方式中，期望的效果是接口和面部表面之间的密封以防止泄漏。在另一实施方式中，期望的效果是用户对治疗的依从性。在另一实施方式中，该方法包括由至少一个移动计算装置收集从用户输入的主观数据，并且接口的选择至少部分地基于该主观数据。在另一实施方式中，该方法包括经由机器学习模块确定与实现期望的效果的接口关联的操作数据的类型。在另一实施方式中，选择的接口包括多种类型的接口中的一种和多种尺寸的接口中的一种。在另一实施方式中，该方法包括基于操作选择的接口接收来自用户的反馈；以及基于不期望的结果，基于期望的效果选择另一接口。在另一实施方式中，不期望的结果是用户对治疗的低依从性、高泄漏、或不令人满意的主观结果数据中的一者。In other embodiments of the above disclosed methods of providing a suitable fitting interface, the interface is a mask. In another embodiment, the respiratory treatment device is configured to provide one or more of positive airway pressure (PAP) or non-invasive ventilation (NIV). In another embodiment, at least one of the respiratory treatment devices includes an audio sensor to collect audio data during operation of at least one of the respiratory treatment devices. In another embodiment, selecting includes analyzing the audio data to determine a corresponding type of interface for at least one of the respiratory treatment devices based on matching the audio data with acoustic signatures of known interfaces. In another embodiment, the selecting includes comparing the user's demographic data to demographic data for a population of users stored in one or more databases. In another embodiment, the operational data includes one of flow rate, motor speed, and treatment pressure. In another embodiment, the facial image is determined from scans from a mobile device including a camera. In another embodiment, the mobile device includes a depth sensor. The camera is a 3D camera, and the facial features are three-dimensional features derived from a meshed surface derived from facial images. In another embodiment, the facial image is a two-dimensional image including landmarks, and the facial features are three-dimensional features derived from the landmarks. In another embodiment, the facial image is one of a plurality of two-dimensional facial images. These facial features are three-dimensional features derived from a 3D deformation model adapted to match facial images. In another embodiment, the facial image includes landmarks related to at least one facial dimension. In another embodiment, facial dimensions include facial height, nasal width, and nasal depth. In another embodiment, the desired effect is a seal between the interface and the facial surface to prevent leakage. In another embodiment, the desired effect is user compliance with treatment. In another embodiment, the method includes collecting, by at least one mobile computing device, subjective data input from a user, and selection of the interface is based at least in part on the subjective data. In another embodiment, the method includes determining, via a machine learning module, a type of operational data associated with an interface that achieves a desired effect. In another embodiment, the selected interface includes one of multiple types of interfaces and one of multiple sizes of interfaces. In another embodiment, the method includes receiving feedback from a user based on an interface selected for operation; and selecting another interface based on a desired effect based on undesirable results. In another embodiment, the undesirable outcome is one of low user compliance with treatment, high leakage, or unsatisfactory subjective outcome data.
在向用户在接口上提供定制适配性的以上公开的方法的其他实施方式中，该接口是可流体联接到呼吸装置。在另一实施方式中，生成输出反馈包括确定建议的动作，如果实施该建议的动作，则该建议的动作将影响特性以改善当前适配性；以及使用移动装置的电子界面来呈现该建议的动作。在另一实施方式中，传感器数据包括来自以下的红外数据：i)无源热传感器；ii)有源热传感器；或iii)i和ii两者。在另一实施方式中，该方法还包括接收与选择的接口在用户的面部上的当前适配性相关联的传感器数据。该传感器数据由移动装置的一个或多个传感器收集。该方法还包括使用该传感器数据生成面部映射。该面部映射指示用户的面部的一个或多个特征。该方法还包括使用传感器数据和面部映射来识别与当前适配性相关联的特性。该特性指示当前适配性的质量，并且该特性与面部映射上的特性位置相关联。该方法还包括基于识别的特性和特性位置生成输出反馈。在另一实施方式中，传感器数据包括指示移动装置的一个或多个传感器与用户的面部之间的一个或多个距离的距离数据。在另一实施方式中，该一个或多个传感器包括：i)接近传感器；ii)基于红外的点阵传感器；iii)LiDAR传感器；iv)基于MEMS微镜投影仪的传感器；或v)i至iv的任何组合。在另一实施方式中，对传感器数据的收集是在：i)在用户戴上接口之前；ii)当用户佩戴具有当前适配性的接口时；iii)在用户移除接口之后；或iii)i、ii和iii的任何组合。在另一实施方式中，该方法还包括接收初始传感器数据。在戴上接口之前，将初始传感器数据与用户的面部相关联。识别特性包括将初始传感器数据与传感器数据进行比较。在另一实施方式中，该特性包括：i)用户的面部上的局部温度；ii)用户的面部上的局部温度变化；iii)用户的面部上的局部颜色；iv)用户的面部上的局部颜色的变化；v)用户的面部上的局部轮廓；vi)用户的面部上的局部轮廓的变化；vii)接口上的局部轮廓；viii)接口上的局部变化；ix)接口上的局部温度；或x)i至ix的任何组合。在另一实施方式中，该特性包括：i)接口相对于用户的面部的一个或多个特征的垂直位置；ii)接口相对于用户的面部的一个或多个特征的水平位置；iii)接口相对于用户的面部的一个或多个特征的旋转取向；iv)接口的识别的特征相对于用户的面部的一个或多个特征之间的距离；或v)i至iv的任何组合。在另一实施方式中，一个或多个传感器包括一个或多个定向传感器，并且传感器数据包括来自该一个或多个定向传感器的定向传感器数据。接收传感器数据包括：当移动装置取向成使得一个或多个定向传感器朝向用户的面部定向时，使用该移动装置扫描用户的面部；以及跟踪对面部的扫描的进展。生成不可见刺激，所述不可见刺激指示对面部的扫描的进展。在另一实施方式中，该方法还包括接收与移动装置的移动相关联的运动数据；以及将该运动数据应用于传感器数据，以考虑到移动装置相对于用户的面部的移动。在另一实施方式中，该方法还包括使用传感器数据生成接口映射。该接口映射指示接口的一个或多个特征相对于面部映射的相对位置。识别特性包括使用该接口映射。在另一实施方式中，一个或多个传感器包括相机，并且传感器数据包括相机数据。该方法还包括当该相机朝向校准表面定向时接收由该相机收集的传感器校准数据；以及基于该传感器校准数据来校准传感器数据的相机数据。在另一实施方式中，该方法还包括使用传感器数据和面部映射来识别附加特性，该附加特性与接口的可能的未来故障相关联。该方法还包括基于识别的附加特性生成输出反馈。输出反馈可用于降低可能的未来故障将发生的可能性或延迟可能的未来故障的发生。在另一实施方式中，该方法还包括在接收传感器数据之前访问与接口在用户的面部上的一个或多个历史适配性相关联的历史传感器数据。识别特性还使用历史传感器数据。在另一实施方式中，该方法还包括使用传感器数据和面部映射生成当前适配性得分。生成输出反馈以提高后续适配性得分。在另一实施方式中，接收传感器数据包括从一个或多个音频传感器接收音频数据。识别特性包括使用该音频数据识别无意泄漏。在另一实施方式中，一个或多个传感器包括相机、音频传感器、和热传感器。传感器数据包括相机数据、音频数据、和热数据。识别特性包括：使用相机数据、音频数据、和热数据中的至少一者来识别潜在的特性；以及使用相机数据、音频数据、和热数据中的至少另一者来确认该潜在的特性。在另一实施方式中，该方法还包括呈现指示待由用户实施的动作的用户指令。该方法还包括接收指示用户已经实施该动作的完成信号。在接收完成信号之前收集传感器数据的第一部分，并且在接收完成信号之后收集传感器数据的第二部分。识别特性包括将传感器数据的第一部分与传感器数据的第二部分进行比较。在另一实施方式中，生成面部映射包括：使用接收的传感器数据识别第一个体和第二个体；将第一个体识别为与接口相关联；以及生成针对第一个体的面部映射。在另一实施方式中，接收传感器数据包括根据接收的传感器数据确定调整数据。该调整数据与以下相关联：i)移动装置的移动，ii)移动装置的固有噪声，iii)用户的呼吸噪声，iv)用户的说话噪声，v)环境照明的变化，vi)检测到的投射在用户的面部上的瞬态阴影，vii)检测到的投射在用户的面部上的瞬态有色光，或viii)i至vii的任何组合。接收传感器数据还包括基于调整数据将调整应用于接收的传感器数据中的至少一些。在另一实施方式中，接收传感器数据包括：接收与一个或多个传感器中的相机相关联的图像数据，该相机在可见光谱中操作；接收与一个或多个传感器中的附加传感器相关联的不稳定数据，该附加传感器是测距传感器或在可见光谱之外操作的图像传感器；确定与图像数据的稳定性相关联的图像稳定性信息；以及使用与图像数据的稳定性相关联的图像稳定性信息来稳定不稳定数据。在另一实施方式中，输出反馈可用于改善当前适配性。在另一实施方式中，该方法还包括使用传感器数据基于当前适配性生成初始得分。该方法还包括接收与接口在用户的面部上的后续适配性相关联的后续传感器数据。后续适配性基于实施输出反馈之后的当前适配性。该方法还包括使用后续传感器数据基于后续适配性生成后续得分；以及评估后续得分，该后续得分指示相对于初始得分的质量改善。在另一实施方式中，识别与当前适配性相关联的特性包括：基于接收的传感器数据确定用户的呼吸模式；基于接收的传感器数据和面部映射确定与用户的面部相关联的热模式；以及使用该呼吸模式和该热模式确定泄漏特性。泄漏特性指示有意通气口泄漏和无意密封泄漏之间的平衡。在另一实施方式中，该一个或多个传感器包括至少两个传感器，该至少两个传感器选自由以下组成的组：i)无源热传感器；ii)有源热传感器；iii)相机；iv)加速度计；v)陀螺仪；vi)电子罗盘；vii)磁力计；viii)压力传感器；ix)麦克风；x)温度传感器；xi)接近传感器；xii)基于红外的点阵传感器；xiii)LiDAR传感器；xiv)基于MEMS微镜投影仪的传感器；xv)基于射频的测距传感器；以及xvi)无线网络接口。在另一实施方式中，该方法包括从呼吸装置的一个或多个附加传感器接收附加传感器数据。识别特性包括使用该附加传感器数据。在另一实施方式中，该方法还包括发送控制信号，该控制信号在被呼吸装置接收时使呼吸装置使用定义参数的集合来操作。当呼吸装置使用该定义参数的集合来操作时收集传感器数据的第一部分，而当呼吸装置不使用该定义参数的集合来操作时收集传感器数据的第二部分。识别特性包括将传感器数据的第一部分与传感器数据的第二部分进行比较。In other embodiments of the above-disclosed methods of providing a custom fit on the interface to the user, the interface is fluidly coupleable to a breathing device. In another embodiment, generating the output feedback includes determining a recommended action that, if implemented, would affect the characteristic to improve current fitness; and using an electronic interface of the mobile device to present the recommended action action. In another embodiment, the sensor data includes infrared data from: i) a passive thermal sensor; ii) an active thermal sensor; or iii) both i and ii. In another embodiment, the method further includes receiving sensor data associated with a current fit of the selected interface on the user's face. The sensor data is collected by one or more sensors of the mobile device. The method also includes generating a facial map using the sensor data. The facial map indicates one or more features of the user's face. The method also includes using sensor data and facial mapping to identify characteristics associated with current fitness. This feature indicates the quality of the current fit, and the feature is associated with the feature location on the face map. The method also includes generating output feedback based on the identified features and feature locations. In another embodiment, the sensor data includes distance data indicative of one or more distances between one or more sensors of the mobile device and the user's face. In another embodiment, the one or more sensors include: i) a proximity sensor; ii) an infrared-based dot matrix sensor; iii) a LiDAR sensor; iv) a MEMS micromirror projector-based sensor; or v) i to any combination of iv. In another embodiment, the sensor data is collected: i) before the user puts on the interface; ii) while the user puts on the interface with the current fit; iii) after the user removes the interface; or iii) Any combination of i, ii and iii. In another embodiment, the method further includes receiving initial sensor data. Initial sensor data is associated with the user's face before the interface is put on. Identifying characteristics involves comparing initial sensor data to sensor data. In another embodiment, the characteristics include: i) local temperature on the user's face; ii) local temperature change on the user's face; iii) local color on the user's face; iv) local color on the user's face Changes in color; v) local contours on the user's face; vi) changes in local contours on the user's face; vii) local contours on the interface; viii) local changes on the interface; ix) local temperature on the interface; or any combination of x)i to ix. In another embodiment, the characteristics include: i) a vertical position of the interface relative to one or more features of the user's face; ii) a horizontal position of the interface relative to one or more features of the user's face; iii) the interface rotational orientation relative to one or more features of the user's face; iv) distance between identified features of the interface relative to one or more features of the user's face; or v) any combination of i to iv. In another embodiment, the one or more sensors include one or more orientation sensors, and the sensor data includes orientation sensor data from the one or more orientation sensors. Receiving sensor data includes using the mobile device to scan the user's face when the mobile device is oriented such that one or more orientation sensors are oriented toward the user's face; and tracking the progress of the scan of the face. An invisible stimulus is generated that indicates the progress of the scan of the face. In another embodiment, the method further includes receiving motion data associated with movement of the mobile device; and applying the motion data to the sensor data to account for movement of the mobile device relative to the user's face. In another embodiment, the method further includes generating an interface map using the sensor data. The interface map indicates the relative position of one or more features of the interface relative to the face map. Identifying features involves using this interface map. In another embodiment, the one or more sensors include a camera and the sensor data includes camera data. The method also includes receiving sensor calibration data collected by the camera when the camera is oriented toward the calibration surface; and calibrating the camera data of the sensor data based on the sensor calibration data. In another embodiment, the method further includes using the sensor data and facial mapping to identify additional characteristics associated with possible future failures of the interface. The method also includes generating output feedback based on the identified additional characteristics. Output feedback can be used to reduce the likelihood that a possible future failure will occur or to delay the occurrence of a possible future failure. In another embodiment, the method further includes accessing historical sensor data associated with one or more historical fits of the interface on the user's face prior to receiving the sensor data. The identification feature also uses historical sensor data. In another embodiment, the method further includes generating a current fitness score using the sensor data and facial mapping. Generate output feedback to improve subsequent fitness scores. In another embodiment, receiving sensor data includes receiving audio data from one or more audio sensors. Identification properties include using this audio data to identify inadvertent leaks. In another embodiment, the one or more sensors include a camera, an audio sensor, and a thermal sensor. Sensor data includes camera data, audio data, and thermal data. Identifying the characteristic includes using at least one of camera data, audio data, and thermal data to identify the potential characteristic; and using at least one other of camera data, audio data, and thermal data to confirm the potential characteristic. In another embodiment, the method further includes presenting a user instruction indicating an action to be performed by the user. The method also includes receiving a completion signal indicating that the user has performed the action. A first portion of the sensor data is collected before the completion signal is received, and a second portion of the sensor data is collected after the completion signal is received. Identifying the characteristics involves comparing a first part of the sensor data with a second part of the sensor data. In another embodiment, generating the facial map includes identifying the first individual and the second individual using the received sensor data; identifying the first individual as associated with the interface; and generating the facial map for the first individual. In another embodiment, receiving sensor data includes determining adjustment data based on the received sensor data. This adjustment data is associated with: i) movement of the mobile device, ii) inherent noise of the mobile device, iii) breathing noise of the user, iv) speaking noise of the user, v) changes in ambient lighting, vi) detected projections A transient shadow on the user's face, vii) a detected transient colored light cast on the user's face, or viii) any combination of i to vii. Receiving the sensor data also includes applying adjustments to at least some of the received sensor data based on the adjustment data. In another embodiment, receiving sensor data includes: receiving image data associated with a camera of one or more sensors operating in the visible spectrum; receiving image data associated with an additional sensor of the one or more sensors. Unstable data, the additional sensor being a ranging sensor or an image sensor operating outside the visible spectrum; determining image stabilization information associated with the stability of the image data; and using image stabilization associated with the stability of the image data information to stabilize unstable data. In another embodiment, output feedback can be used to improve current fitness. In another embodiment, the method further includes using the sensor data to generate an initial score based on the current fitness. The method also includes receiving subsequent sensor data associated with subsequent fit of the interface on the user's face. Subsequent fitness is based on the current fitness after output feedback is implemented. The method also includes generating a subsequent score based on the subsequent fit using subsequent sensor data; and evaluating the subsequent score indicating an improvement in quality relative to the initial score. In another embodiment, identifying characteristics associated with the current fit includes: determining a breathing pattern of the user based on received sensor data; determining a thermal pattern associated with the user's face based on the received sensor data and facial mapping; and The breathing pattern and the thermal pattern are used to determine leak characteristics. Leakage characteristics indicate the balance between intentional vent leakage and unintentional seal leakage. In another embodiment, the one or more sensors include at least two sensors selected from the group consisting of: i) passive thermal sensors; ii) active thermal sensors; iii) cameras; iv )Accelerometer; v) Gyroscope; vi) Electronic compass; vii) Magnetometer; viii) Pressure sensor; ix) Microphone; x) Temperature sensor; xi) Proximity sensor; xii) Infrared-based dot matrix sensor; xiii) LiDAR Sensor; xiv) MEMS micromirror projector-based sensor; xv) RF-based ranging sensor; and xvi) wireless network interface. In another embodiment, the method includes receiving additional sensor data from one or more additional sensors of the respiratory device. Identifying features includes using this additional sensor data. In another embodiment, the method further includes sending a control signal that, when received by the respiratory device, causes the respiratory device to operate using a defined set of parameters. A first portion of the sensor data is collected when the respiratory device operates using the defined set of parameters, and a second portion of the sensor data is collected when the respiratory device does not operate using the defined set of parameters. Identifying the characteristics involves comparing a first part of the sensor data with a second part of the sensor data.
图1示出了包括用户10的系统，该用户10佩戴全面部面罩(FFM)形式的用户接口100，该用户10从呼吸治疗装置(诸如气道正压通气(PAP)装置，并且特别是呼吸压力治疗(RPT)装置40)接收正压空气供应。来自RPT装置40的空气在加湿器60中加湿，并沿空气回路50流向用户10。Figure 1 illustrates a system including a user 10 who wears a user interface 100 in the form of a full face mask (FFM), who receives a response from a respiratory therapy device, such as a positive airway pressure (PAP) device, and in particular a respiratory therapy device. Pressure therapy (RPT) device 40) receives a supply of positive pressure air. The air from the RPT device 40 is humidified in the humidifier 60 and flows along the air circuit 50 to the user 10 .
在该实例中，本文所述的呼吸治疗装置可包括被配置成提供气道正压通气(PAP)、无创通气(NIV)或有创通气中的一种或多种的任何呼吸治疗装置。在该实例中，PAP装置可以是持续气道正压通气(CPAP)装置、自动气道正压通气装置(APAP)、双水平或可变气道正压通气装置(BPAP或VPAP)或其任何组合。CPAP装置向用户递送预定空气压力(例如，由睡眠医生确定)。APAP装置基于例如，与用户相关联的呼吸数据来自动改变递送到用户的空气压力。BPAP或VPAP装置被配置成递送第一预定压力(例如，吸气气道正压通气或IPAP)和低于第一预定压力的第二预定压力(例如，呼气气道正压通气或EPAP)。In this example, the respiratory treatment devices described herein may include any respiratory treatment device configured to provide one or more of positive airway pressure (PAP), non-invasive ventilation (NIV), or invasive ventilation. In this example, the PAP device may be a continuous positive airway pressure (CPAP) device, an automatic positive airway pressure device (APAP), a bilevel or variable positive airway pressure device (BPAP or VPAP), or any combination. The CPAP device delivers a predetermined air pressure to the user (eg, determined by a sleep physician). The APAP device automatically changes the air pressure delivered to the user based on, for example, respiratory data associated with the user. The BPAP or VPAP device is configured to deliver a first predetermined pressure (eg, inspiratory positive airway pressure or IPAP) and a second predetermined pressure less than the first predetermined pressure (eg, expiratory positive airway pressure or EPAP) .
图2A描绘了根据本技术的一个方面的用户接口100，该用户接口100包括以下功能方面：密封形成结构160、充气室120、定位和稳定结构130、通气口140、前额支架150、用于连接到图1中的空气回路50的一种形式的连接端口170。在一些形式中，功能方面可以由一个或多个物理部件来提供。在一些形式中，一个物理部件可提供一个或多个功能方面。在使用时，密封形成结构160被布置成围绕用户气道的入口，以便有利于将正压空气供应至气道。2A depicts a user interface 100 including the following functional aspects: seal-forming structure 160, plenum 120, positioning and stabilizing structure 130, vent 140, forehead support 150, for connection, in accordance with one aspect of the present technology. One form of connection port 170 to air circuit 50 in FIG. 1 . In some forms, functional aspects may be provided by one or more physical components. In some forms, a physical component may provide one or more functional aspects. In use, the seal-forming structure 160 is disposed about the entrance to the user's airway to facilitate the supply of positive pressure air to the airway.
在本技术的一种形式中，密封形成结构160提供密封形成表面，并可附加地提供缓冲功能。根据本技术的密封形成结构160可由诸如硅酮的柔软、柔性和有回弹力的材料构造而成。在一种形式中，无创用户接口100的密封形成部分包括一对鼻扑或鼻枕，每个鼻扑或鼻枕被构造和布置成与用户的鼻的相应的鼻孔形成密封。In one form of the present technology, seal-forming structure 160 provides a seal-forming surface and may additionally provide cushioning functionality. Seal-forming structure 160 in accordance with the present technology may be constructed from soft, flexible, and resilient materials such as silicone. In one form, the seal-forming portion of the non-invasive user interface 100 includes a pair of nose puffs or pillows, each nose puff or pillow constructed and arranged to form a seal with a corresponding nostril of the user's nose.
根据本技术的鼻枕包括：截头圆锥体，该截头圆锥体的至少一部分在用户的鼻的底面上形成密封；柄；在截头圆锥体底面上并且将截头圆锥体连接到柄的柔性分区。此外，本技术的鼻枕连接的结构包括邻近柄底部的柔性分区。柔性分区可共同作用以有利于通用连接结构，该通用连接结构能够随着截头圆锥体和鼻枕连接的结构之间的位移和角度两者的相对移动进行适应。例如，可朝向柄连接的结构轴向移动截头圆锥体的位置。A nasal pillow according to the present technology includes: a frustocone with at least a portion of the frustocone forming a seal on the bottom surface of the user's nose; a handle; Flexible partitioning. Additionally, the structure of the nasal pillow connection of the present technology includes a flexible partition adjacent the base of the handle. The flexible partitions may cooperate to facilitate a universal connection structure that is capable of adapting with relative movement in both displacement and angle between the frustoconical and nasal pillow connected structures. For example, the position of the frustum can be moved axially towards the structure of the stem connection.
在一种形式中，无创用户接口100包括密封形成部分，该密封形成部分在使用中在用户面部的上部唇分区(即，唇上部)上形成密封。在一种形式中，无创用户接口100包括密封形成部分，该密封形成部分在使用中在用户面部的下巴分区上形成密封。In one form, the non-invasive user interface 100 includes a seal-forming portion that, in use, forms a seal on the upper lip region of the user's face (ie, the upper lip). In one form, the non-invasive user interface 100 includes a seal-forming portion that, in use, forms a seal on the chin area of the user's face.
优选地充气室120具有周边，该周边成形为与在使用时将形成密封的分区中的普通人面部的表面轮廓互补。在使用时，充气室120的边界边缘被定位成与面部的邻近表面靠的很近。通过密封形成结构160提供与面部的实际接触。密封形成结构160可在使用时沿充气室120的整个周边延伸。Preferably the plenum 120 has a perimeter shaped to complement the surface contours of an average person's face in a zone that will form a seal when in use. In use, the bounding edges of the plenum 120 are positioned in close proximity to adjacent surfaces of the face. Actual contact with the face is provided by the seal-forming structure 160 . The seal-forming structure 160 may extend along the entire perimeter of the plenum 120 in use.
优选地本技术的用户接口100的密封形成结构160可在使用时通过定位和稳定结构130而保持在密封位置中。The seal-forming structure 160 of the user interface 100 of the present technology is preferably maintained in a sealed position during use by the positioning and stabilizing structure 130 .
在一种形式中，用户接口100包括为允许冲洗呼出的二氧化碳而构造和布置的通气口140。根据本技术的通气口140的一种形式包括多个孔，例如，约20到约80个孔，或约40到约60个孔，或约45到约55个孔。In one form, the user interface 100 includes a vent 140 constructed and arranged to allow flushing of exhaled carbon dioxide. One form of vent 140 in accordance with the present technology includes a plurality of holes, for example, about 20 to about 80 holes, or about 40 to about 60 holes, or about 45 to about 55 holes.
图3A示出了包括内眦、鼻翼、鼻唇沟、唇上部和唇下部、上部唇红部和下部唇红部以及唇角点的人面部的前视图。还示出了嘴宽度，将头部分成左部分和右部分的矢状面，以及定向指示器。定向指示器指示径向向内/向外和上/下方向。图3B示出了人面部的侧视图，包括眉间点、鼻梁点、鼻脊、鼻突点、鼻下点、唇上部和唇下部、颏上点、鼻翼嵴点，以及耳上点和耳下点。还示出了指示上/下和前/后方向的定向指示器。图3C示出了具有识别的数个特征的鼻的底部视图，包括鼻唇沟、唇下部、上部唇红部、鼻孔、鼻下点、鼻小柱、鼻突点、鼻孔的长轴和矢状面。Figure 3A shows a front view of the human face including the medial canthus, nasal alar, nasolabial fold, upper and lower lip portions, upper and lower vermilion portions, and lip corners. Also shown are the width of the mouth, the sagittal plane dividing the head into left and right parts, and orientation indicators. Orientation indicators indicate radial inward/outward and up/down directions. Figure 3B shows a side view of the human face, including the glabella point, the nasal bridge point, the nasal ridge, the nasal process point, the subnasal point, the upper and lower labial parts, the supramental point, the alar ridge point, as well as the supraauricular point and the ear point. Lower point. Orientation indicators indicating up/down and fore/aft directions are also shown. Figure 3C shows a bottom view of the nose with several features identified, including the nasolabial folds, sublabium, upper vermilion, nostrils, subnasal point, columella, nasal prominence, long axis and sagittal of the nostrils. shape surface.
下面更详细地说明图3A至图3C中示出的人面部的特征。The features of the human face shown in FIGS. 3A to 3C are explained in more detail below.
鼻翼(Ala)：每个鼻孔的外部外壁或“翼”(复数：鼻翼(alar))Ala: The outer wall or "wing" of each nostril (plural: alar)
鼻翼端：鼻翼上的最外侧点。Alar tip: The outermost point on the nose.
鼻翼弯曲(或鼻翼嵴)点：每个鼻翼的弯曲基线中最后方的点，在由鼻翼与面颊的结合形成的褶皱中发现。Alar curvature (or alar ridge) point: The most posterior point in the curvature baseline of each alar, found in the fold formed by the union of the alar and cheek.
耳廓：耳朵的整个外部可见部分。Auricle: The entire external visible part of the ear.
鼻小柱：分离鼻孔且从鼻突点延伸到上部唇的皮肤条。Columella: The strip of skin that separates the nostrils and extends from the nasal prominence to the upper lip.
鼻小柱角：通过鼻孔中点绘制的线与垂直于法兰克福(Frankfort)平面绘制的线(同时两线相交于鼻下点)之间的夹角。Columella angle: the angle between a line drawn through the midpoint of the nostril and a line drawn perpendicular to the Frankfort plane (both lines intersect at the subnasal point).
眉间点：位于软组织上，前额正中矢状面中最突出的点。Glabellar point: The most prominent point on the soft tissue in the mid-sagittal plane of the forehead.
鼻孔(鼻眼)：形成鼻腔入口的近似椭圆形的孔。鼻孔(nare)的单数形是鼻孔(naris)(鼻眼)。鼻孔由鼻中隔分开。Nostrils (nostrils): The approximately oval holes that form the entrance to the nasal cavity. The singular form of nostril (nare) is naris (nostril). The nostrils are separated by the nasal septum.
鼻唇沟或鼻唇褶：从鼻的每一侧延伸到嘴角，将面颊与上部唇分开的皮肤褶或沟。Nasolabial folds or nasolabial folds: The folds or grooves of skin that extend from each side of the nose to the corners of the mouth and separate the cheeks from the upper lips.
鼻唇角：鼻小柱与上部唇(同时相交于鼻下点)之间的角。Nasolabial angle: The angle between the columella and the upper lip (which also intersects at the subnasal point).
耳下点：耳廓附接到面部皮肤的最低点。Infraauricular point: The lowest point where the auricle attaches to the facial skin.
耳上点：耳廓附接到面部皮肤的最高点。Supraauricular point: The highest point where the auricle attaches to the facial skin.
鼻突点：鼻的最突出的点或尖端，其可以在头部的其余部分的侧视图中被识别。Nasal Point: The most prominent point or tip of the nose, which can be identified in side view over the rest of the head.
人中：从鼻中隔的下部边界延伸到上部唇分区中的唇顶部的中线沟。Philtrum: A midline sulcus extending from the inferior border of the nasal septum to the roof of the lip in the upper labial division.
颏前点：位于软组织上，下巴的最前中点。Premental point: Located on the soft tissue, the most anterior midpoint of the chin.
脊(鼻的)：鼻脊是鼻的从鼻梁点延伸到鼻突点的中线突起。Ridge (nasal): The nasal ridge is the midline protrusion of the nose extending from the bridge point to the nasal protrusion point.
矢状面：从前(前面)到后(后面)经过的将身体分为右半部和左半部的垂直面。Sagittal plane: The vertical plane that passes from front (front) to back (back) and divides the body into right and left halves.
鼻梁点：位于软组织上，叠加于额鼻缝区域的最凹点。Bridge point: The most concave point located on the soft tissue and superimposed on the frontonasal suture area.
中隔软骨(鼻)：鼻中隔软骨形成中隔的一部分并分开鼻腔的前部。Septal cartilage (nose): The septal cartilage forms part of the septum and separates the front of the nasal cavity.
后上侧片：在鼻翼基部下部边缘处的点，在此处鼻翼基部与上(上部)唇的皮肤接合。Posterosuperior lateral panel: The point on the lower edge of the alar base where the alar base joins the skin of the upper (upper) lip.
鼻下点：位于软组织上，正中矢状面中鼻小柱与上部唇交汇处的点。Subnasal point: The point located on the soft tissue at the intersection of the columella and the upper lip in the mid-sagittal plane.
颏上点：下部唇的中线中位于下唇中点与软组织颏前点之间的最大凹度的点。Supramental point: The point of maximum concavity in the midline of the lower lip between the midpoint of the lower lip and the premental point of the soft tissue.
如将在下面解释的，存在来自面部的数个关键维度，该数个关键维度可用于选择诸如图1中的面罩100的用户接口的尺寸制定。在该实例中，存在包括面部高度、鼻宽度、和鼻深度的三个维度。图3A至图3B示出了表示面部高度的线3010。如在图3A中可以看到的，面部高度是鼻梁点到颏上点之间的距离。图3A中的线3020表示鼻宽度，鼻宽度可以是鼻的鼻翼端(例如鼻翼上的最左侧点和最右侧点)之间的距离。图3B中的线3030表示鼻深度，鼻深度可以是在平行于矢状面的方向上鼻突点和鼻翼嵴点之间的距离。As will be explained below, there are several key dimensions from the face that can be used to select sizing of a user interface such as mask 100 in FIG. 1 . In this example, there are three dimensions including facial height, nose width, and nose depth. Figures 3A-3B show a line 3010 representing facial height. As can be seen in Figure 3A, facial height is the distance between the bridge of the nose point and the supramental point. Line 3020 in Figure 3A represents nose width, which may be the distance between the alar ends of the nose (eg, the leftmost point and the rightmost point on the alar). Line 3030 in Figure 3B represents nasal depth, which may be the distance between the nasal process point and the alar crest point in a direction parallel to the sagittal plane.
图4A示出了根据本技术的一个方面的示例RPT装置40的部件的放大视图，该示例RPT装置40包括机械、气动和/或电气部件，并且被配置为执行一个或多个算法，诸如本文中整体地或部分描述的方法中的任一种。图4B示出了示例RPT装置40的框图。图4C示出了示例RPT装置40的电控制部件的框图。上游和下游的方向参考鼓风机和用户接口来指示。该鼓风机被定义为该用户接口的上游并且该用户接口被定义为该鼓风机的下游，而不管在任何特定时刻的实际流动方向。位于鼓风机和用户接口之间的气动路径内的物件位于鼓风机的下游和用户接口的上游。RPT装置40可被配置成生成递送至用户气道的气流，诸如以治疗一种或多种呼吸病症。4A illustrates an enlarged view of components of an example RPT device 40 that includes mechanical, pneumatic, and/or electrical components and is configured to perform one or more algorithms, such as herein, in accordance with one aspect of the present technology. any of the methods described in whole or in part. Figure 4B shows a block diagram of an example RPT device 40. 4C shows a block diagram of the electrical control components of the example RPT device 40. Upstream and downstream directions are indicated with reference to the blower and user interface. The blower is defined upstream of the user interface and the user interface is defined downstream of the blower, regardless of the actual flow direction at any particular moment. Objects located in the pneumatic path between the blower and the user interface are located downstream of the blower and upstream of the user interface. RPT device 40 may be configured to generate airflow delivered to the user's airway, such as to treat one or more respiratory conditions.
RPT装置40可具有外部壳体4010，该外部壳体4010形成为两部分：上部部分4012和下部部分4014。此外，外部壳体4010可包括一个或多个面板4015。RPT装置40包括底盘4016，该底盘4016支撑RPT装置40的一个或多个内部部件。RPT装置40可包括手柄4018。The RPT device 40 may have an outer housing 4010 formed in two parts: an upper part 4012 and a lower part 4014. Additionally, outer housing 4010 may include one or more panels 4015. RPT device 40 includes a chassis 4016 that supports one or more internal components of RPT device 40 . RPT device 40 may include a handle 4018.
RPT装置40的气动路径可以包括一个或多个空气路径物件，例如入口空气过滤器4112、入口消音器4122、能够供应正压空气的压力发生器4140(例如，鼓风机4142)、出口消音器4124和一个或多个换能器4270，诸如压力传感器4272、流量传感器4274和电动机速度传感器4276。The pneumatic path of the RPT device 40 may include one or more air path items, such as an inlet air filter 4112, an inlet muffler 4122, a pressure generator 4140 capable of supplying positive pressure air (eg, a blower 4142), an outlet muffler 4124, and One or more transducers 4270, such as pressure sensor 4272, flow sensor 4274, and motor speed sensor 4276.
空气路径物件中的一个或多个可以位于被称为气动块4020的可拆卸整体结构内。气动块4020可位于外部壳体4010内。在一种形式中，气动块4020由底盘4016支撑，或作为底盘4016的一部分形成。One or more of the air path items may be located within a removable unitary structure referred to as pneumatic block 4020. Pneumatic block 4020 may be located within outer housing 4010. In one form, pneumatic mass 4020 is supported by, or formed as part of, chassis 4016 .
RPT装置40可以具有电源4210、一个或多个输入装置4220、中央控制器4230、压力发生器4140、数据通信接口4280和一个或多个输出装置4290。可以为治疗装置提供单独的控制器。电气部件4200可安装在单个印刷电路板组件(PCBA)4202上。在一种替代形式中，RPT装置40可以包括多于一个PCBA 4202。诸如一个或多个保护电路4250、换能器4270、数据通信接口4280和存储装置的其他部件也可以安装在PCBA 4202上。RPT device 40 may have a power supply 4210, one or more input devices 4220, a central controller 4230, a pressure generator 4140, a data communication interface 4280, and one or more output devices 4290. A separate controller can be provided for the treatment device. Electrical components 4200 may be mounted on a single printed circuit board assembly (PCBA) 4202. In an alternative form, RPT device 40 may include more than one PCBA 4202. Other components such as one or more protection circuits 4250, transducers 4270, data communication interfaces 4280, and storage devices may also be mounted on PCBA 4202.
RPT装置可在整体单元中包括以下部件中的一个或多个。在一种替代形式中，以下部件中的一个或多个可定位为相应的单独单元。An RPT device may include one or more of the following components in an integral unit. In an alternative form, one or more of the following components may be located as respective separate units.
根据本技术的一种形式的RPT装置可包括一个空气过滤器4110，或多个空气过滤器4110。在一种形式中，入口空气过滤器4112位于压力发生器4140的气动路径上游的起点处。在一种形式中，出口空气过滤器4114，例如抗菌过滤器位于气动块4020的出口与用户接口100之间。An RPT device according to one form of the present technology may include an air filter 4110, or a plurality of air filters 4110. In one form, the inlet air filter 4112 is located at the beginning of the pneumatic path upstream of the pressure generator 4140. In one form, an outlet air filter 4114, such as an antimicrobial filter, is located between the outlet of the pneumatic block 4020 and the user interface 100.
根据本技术的一种形式的RPT装置可包括一个消音器4120，或多个消音器4120。在本技术的一种形式中，入口消音器4122位于压力发生器4140的气动路径上游中。在本技术的一种形式中，出口消音器4124位于压力发生器4140和图1中的用户接口100之间的气动路径中。An RPT device according to one form of the present technology may include a silencer 4120, or a plurality of silencers 4120. In one form of the present technology, an inlet silencer 4122 is located in the pneumatic path upstream of the pressure generator 4140. In one form of the present technology, an outlet silencer 4124 is located in the pneumatic path between the pressure generator 4140 and the user interface 100 in FIG. 1 .
在本技术的一种形式中，用于产生正压下的空气流或空气供应的压力发生器4140为可控鼓风机4142。例如，鼓风机4142可包括具有一个或多个叶轮的无刷DC电动机4144。这些叶轮可以位于蜗壳中。鼓风机能够例如以高达约120升/分钟的速率，并以从约4cm H2O至约20cm H2O范围内的正压或以高达约30cm H2O的其他形式递送空气供应。鼓风机可如以下专利或专利申请：美国专利第7,866,944号；美国专利第8,638,014号；美国专利第8,636,479号；以及PCT专利申请公布第WO 2013/020167号中的任一个所述，这些专利或专利申请的内容通过引用整体并入本文。In one form of the present technology, the pressure generator 4140 for generating a flow or supply of air at positive pressure is a controllable blower 4142. For example, blower 4142 may include a brushless DC motor 4144 with one or more impellers. These impellers can be located in the volute. The blower can, for example, deliver a supply of air at a rate of up to about 120 liters per minute and at a positive pressure ranging from about 4 cm H2O to about 20 cm H2O or in other forms up to about 30 cm H2O. The blower may be as described in any of the following patents or patent applications: U.S. Patent No. 7,866,944; U.S. Patent No. 8,638,014; U.S. Patent No. 8,636,479; and PCT Patent Application Publication No. WO 2013/020167, which patents or patent applications The contents of are incorporated herein by reference in their entirety.
压力发生器4140在治疗装置控制器4240的控制下。换言之，压力发生器4140可为活塞驱动泵、与高压源连接的压力调节器(例如，压缩空气存贮室)或波纹管。Pressure generator 4140 is under control of treatment device controller 4240. In other words, the pressure generator 4140 may be a piston driven pump, a pressure regulator connected to a high pressure source (eg, a compressed air storage chamber), or a bellows.
根据本技术一个方面的空气回路4170为导管或管子，该导管或管子在使用时被构造和布置成允许加压空气流在两个部件，诸如加湿器60和用户接口100之间行进。具体地，空气回路4170可以与加湿器60的出口和用户接口100的充气室120流体连通。Air circuit 4170 according to one aspect of the technology is a duct or tube that, in use, is constructed and arranged to allow a flow of pressurized air to travel between two components, such as humidifier 60 and user interface 100 . Specifically, air circuit 4170 may be in fluid communication with the outlet of humidifier 60 and plenum 120 of user interface 100 .
在本技术的一种形式中，反溢回阀4160位于加湿器60与气动块4020之间。反溢回阀被构造和布置成降低水将从加湿器60向上游流动到例如电动机4144的风险。In one form of the present technology, a backflow valve 4160 is located between the humidifier 60 and the pneumatic block 4020. The backflow valve is constructed and arranged to reduce the risk that water will flow upstream from the humidifier 60 to, for example, the electric motor 4144.
电源4210可位于RPT装置40的外部壳体4010的内部或外部。在本技术的一种形式中，电源4210仅向RPT装置40提供电力。在本技术的另一形式中，电源4210向RPT装置40和加湿器60两者提供电力。The power supply 4210 may be located inside or outside the outer housing 4010 of the RPT device 40 . In one form of the present technology, power supply 4210 provides power only to RPT device 40. In another form of the present technology, power supply 4210 provides power to both RPT device 40 and humidifier 60.
RT系统可以包括被配置成测量与RT系统、其用户和/或其环境有关的任何数量的参数中的一个或多个的一个或多个换能器(传感器)4270。换能器可以被配置成产生表示换能器被配置成测量的一个或多个参数的输出信号。The RT system may include one or more transducers (sensors) 4270 configured to measure one or more of any number of parameters related to the RT system, its user, and/or its environment. The transducer may be configured to produce an output signal representative of one or more parameters that the transducer is configured to measure.
该输出信号可以是电信号、磁信号、机械信号、视觉信号、光信号、声音信号或本领域已知的任何数量的其他信号中的一者或多者。The output signal may be one or more of an electrical signal, a magnetic signal, a mechanical signal, a visual signal, an optical signal, an acoustic signal, or any number of other signals known in the art.
换能器可以与RT系统的另一部件集成，其中一个示例性布置是换能器在RPT装置内部。换能器可以基本上是RT系统的‘独立’部件，该换能器的示例性布置是换能器在RPT装置外部。The transducer may be integrated with another component of the RT system, with one exemplary arrangement having the transducer internal to the RPT device. The transducer may be essentially a 'stand-alone' component of the RT system, an exemplary arrangement of which is that the transducer is external to the RPT device.
换能器可以被配置成将其输出信号传送到RT系统的一个或多个部件，诸如RPT装置、本地外部装置或远程外部装置。外部换能器可以例如位于用户接口上，或者位于诸如智能电话的外部计算装置中。外部换能器可以位于例如空气回路(例如用户接口)上或形成空气回路的一部分。The transducer may be configured to transmit its output signal to one or more components of the RT system, such as an RPT device, a local external device, or a remote external device. The external transducer may be located on a user interface, for example, or in an external computing device such as a smartphone. The external transducer may be located, for example, on or form part of an air circuit (eg, a user interface).
图4D示出了绘示的根据本公开的一些实施方式的系统4300。该系统4300包括控制系统4310，该控制系统4310包括处理器4312、存储器装置4314、电子接口4316和一个或多个传感器4270。在一些实施方式中，该系统4300还可选地包括呼吸治疗系统4320，该呼吸治疗系统4320可以是图2中的系统，该系统包括RPT装置40，诸如移动装置234的用户装置和活动跟踪器4322。装置234可以包括显示器4344。在一些情况下，系统4300中的一些或大部分可被实现为移动装置232、RPT装置40，或者在诸如外部计算装置的其他外部装置中。如上解释，呼吸治疗系统4320包括RPT装置40、用户或用户接口100、导管4326、诸如输出4290的显示器和加湿器60。Figure 4D illustrates an illustrated system 4300 in accordance with some embodiments of the present disclosure. The system 4300 includes a control system 4310 including a processor 4312, a memory device 4314, an electronic interface 4316, and one or more sensors 4270. In some embodiments, the system 4300 optionally further includes a respiratory therapy system 4320, which may be the system of FIG. 2 including the RPT device 40, a user device such as the mobile device 234, and an activity tracker. 4322. Device 234 may include display 4344. In some cases, some or most of system 4300 may be implemented as mobile device 232, RPT device 40, or in other external devices such as external computing devices. As explained above, respiratory therapy system 4320 includes RPT device 40, user or user interface 100, conduit 4326, display such as output 4290, and humidifier 60.
一个或多个传感器或换能器4270可被构造和布置成生成表示诸如流速、压力或温度的空气特性的信号。空气可以是从RPT装置到用户的空气流，从用户到大气的空气流，环境空气或任何其他空气。这些信号可以表示在特定点处的空气流的特性，诸如RPT装置和用户之间的气动路径中的空气流。在本技术的一种形式中，一个或多个换能器4270位于RPT装置的气动路径中，诸如位于加湿器60的下游。One or more sensors or transducers 4270 may be constructed and arranged to generate signals representative of air characteristics such as flow rate, pressure, or temperature. The air can be air flow from the RPT device to the user, air flow from the user to the atmosphere, ambient air, or any other air. These signals may represent characteristics of the air flow at a specific point, such as the air flow in the pneumatic path between the RPT device and the user. In one form of the present technology, one or more transducers 4270 are located in the pneumatic path of the RPT device, such as downstream of the humidifier 60 .
根据本技术的一个方面，一个或多个换能器4270包括位于与气动路径流体连通的压力传感器。合适的压力传感器的实例是来自霍尼韦尔(HONEYWELL)ASDX系列的换能器。替代性合适的压力传感器是来自通用电气公司(GENERAL ELECTRIC)的NPA系列的换能器。在一种实施方式中，压力传感器位于邻近加湿器60的出口的空气回路4170中。According to one aspect of the present technology, one or more transducers 4270 include a pressure sensor located in fluid communication with the pneumatic path. Examples of suitable pressure sensors are transducers from the HONEYWELL ASDX series. An alternative suitable pressure sensor is the NPA series transducer from GENERAL ELECTRIC. In one embodiment, the pressure sensor is located in the air circuit 4170 adjacent the outlet of the humidifier 60 .
声学/音频传感器4278(诸如麦克风压力传感器4278)被配置成生成表示空气回路4170内的压力变化的声音信号。“声学传感器”或“音频传感器”是可互换的术语，并且涉及可以检测人听得见和/或听不到的声音的传感器。来自音频传感器4278的声音信号可以由中央控制器4230接收，用于如由下述一个或多个算法配置的声学处理和分析。音频传感器4278可以直接暴露于空气路径以对声音更敏感，或者可以封装在柔性膜材料的薄层后面。该膜可用于保护音频传感器4278免受热和/或湿度的影响。或者，音频传感器4278可以联接到RPT装置40、用户接口100，或者导管或外部用户装置或集成在RPT装置40、用户接口100，或者导管或外部用户装置中。An acoustic/audio sensor 4278 (such as a microphone pressure sensor 4278) is configured to generate an acoustic signal representative of pressure changes within the air circuit 4170. "Acoustic sensor" or "audio sensor" are terms that are interchangeable and refer to sensors that can detect sounds that are audible and/or inaudible to humans. Sound signals from audio sensors 4278 may be received by central controller 4230 for acoustic processing and analysis as configured by one or more algorithms described below. The audio sensor 4278 may be directly exposed to the air path to be more sensitive to sound, or may be encapsulated behind a thin layer of flexible membrane material. This film can be used to protect the audio sensor 4278 from heat and/or humidity. Alternatively, audio sensor 4278 may be coupled to or integrated within RPT device 40, user interface 100, or catheter or external user device.
由音频传感器4278生成的音频数据可再现为一个或多个声音(例如，来自用户10的声音)。来自音频传感器4278的音频数据还可用于识别(例如，使用中央控制器4230)或确认与用户接口相关联的特性，诸如从阀逸出的空气的声音。The audio data generated by audio sensor 4278 may be reproduced as one or more sounds (eg, sounds from user 10). Audio data from audio sensor 4278 may also be used to identify (eg, using central controller 4230) or confirm characteristics associated with the user interface, such as the sound of air escaping from a valve.
扬声器可以输出用户(诸如用户10)听得见的声波。该扬声器可用于例如提供音频反馈，诸如指示如何操纵RPT装置40或另一装置以获得期望的传感器数据，或者指示传感器数据的收集何时充分地完成。在一些实施方式中，该扬声器可用于将由音频传感器4278生成的音频数据传送给用户。该扬声器可以联接到RPT装置40、用户接口100、导管或外部装置或集成在RPT装置40、用户接口100、导管或外部装置中。The speaker may output sound waves that are audible to a user (such as user 10). The speaker may be used, for example, to provide audio feedback, such as indicating how to maneuver RPT device 40 or another device to obtain desired sensor data, or indicating when collection of sensor data is sufficiently complete. In some implementations, the speaker may be used to communicate audio data generated by audio sensor 4278 to the user. The speaker may be coupled to or integrated into the RPT device 40, user interface 100, conduit, or external device.
音频传感器4278和扬声器可以用作单独的装置。在一些实施方式中，音频传感器4278和扬声器可以组合成声学传感器(例如，SONAR传感器)，如在例如WO 2018/050913和WO2020/104465中所描述的，两个专利中的每一个在此通过引用整体并入本文。在此类实施方式中，扬声器以预定间隔生成或发射声波，并且音频传感器4278检测来自扬声器的发射声波的反射。由扬声器生成或发射的声波具有人耳听不到的频率(例如，低于20Hz或高于约18kHz)，以便不干扰用户10。至少部分地基于来自音频传感器4278和/或扬声器的数据，控制系统可以确定关于用户和/或用户接口100的位置信息(例如，用户面部的位置、用户面部上的特征的位置、用户接口100的位置、用户接口100上的特征的位置)、生理参数(例如，呼吸速率)等。在此类上下文中，声纳传感器可以被理解为涉及主动声感测，诸如通过产生和/或发射超声和/或低频超声感测信号(例如，在例如，约17-23kHz、18-22kHz或17-18kHz的频率范围内)通过空气。这种系统可以相对于上面提到的WO 2018/050913和WO 2020/104465来考虑，两个专利中的每一者在此都通过引用整体并入本文。在一些实施方式中，可以使用附加麦克风压力传感器。Audio sensor 4278 and speaker can be used as separate devices. In some embodiments, the audio sensor 4278 and the speaker may be combined into an acoustic sensor (e.g., a SONAR sensor), as described, for example, in WO 2018/050913 and WO 2020/104465, each of which is incorporated herein by reference. Incorporated into this article in its entirety. In such implementations, the speakers generate or emit sound waves at predetermined intervals, and the audio sensor 4278 detects reflections of the emitted sound waves from the speakers. The sound waves generated or emitted by the speakers have frequencies that are inaudible to the human ear (eg, below 20 Hz or above about 18 kHz) so as not to disturb the user 10 . Based at least in part on data from the audio sensor 4278 and/or the speaker, the control system may determine location information about the user and/or the user interface 100 (e.g., the location of the user's face, the location of features on the user's face, the location of the user interface 100 location, location of a feature on the user interface 100), physiological parameters (eg, breathing rate), etc. In such contexts, sonar sensors may be understood to involve active acoustic sensing, such as by generating and/or transmitting ultrasonic and/or low frequency ultrasonic sensing signals (e.g., at, for example, about 17-23 kHz, 18-22 kHz, or 17-18kHz frequency range) through the air. Such a system may be considered with respect to the above-mentioned WO 2018/050913 and WO 2020/104465, each of which is hereby incorporated by reference in its entirety. In some implementations, additional microphone pressure sensors may be used.
来自诸如压力传感器4272、流量传感器4274、电动机速度传感器4276和音频传感器4278的换能器4270的数据可以由中央控制器4230周期性地收集。此类数据通常涉及RPT装置40的操作状态。在该实例中，中央控制器4230以专有数据格式编码来自传感器的此类数据。该数据也可以以标准化数据格式编码。Data from transducers 4270 such as pressure sensor 4272, flow sensor 4274, motor speed sensor 4276, and audio sensor 4278 may be collected periodically by the central controller 4230. Such data typically relates to the operating status of the RPT device 40 . In this example, the central controller 4230 encodes such data from the sensors in a proprietary data format. This data can also be encoded in a standardized data format.
一个或多个传感器或换能器4270也可以包括温度传感器4330、运动传感器4332、扬声器4334、射频(RF)接收器4336、RF发射器4338、相机4340、红外传感器4342(例如无源红外传感器或有源红外传感器)、光电容积图(PPG)传感器4344、心电图(ECG)传感器4346、脑电图(EEG)传感器4348、电容传感器4350、力传感器4352、应变仪传感器4354、肌电图(EMG)传感器4356、氧传感器4358、分析物传感器4360、水分传感器4362、LiDAR传感器4364或其任何组合。通常，一个或多个传感器或换能器4270中的每一个被配置成输出接收并存储在存储器装置中的传感器数据。One or more sensors or transducers 4270 may also include a temperature sensor 4330, a motion sensor 4332, a speaker 4334, a radio frequency (RF) receiver 4336, an RF transmitter 4338, a camera 4340, an infrared sensor 4342 (e.g., a passive infrared sensor or Active infrared sensor), Photoplethysmography (PPG) sensor 4344, Electrocardiogram (ECG) sensor 4346, Electroencephalogram (EEG) sensor 4348, Capacitive sensor 4350, Force sensor 4352, Strain gauge sensor 4354, Electromyography (EMG) Sensor 4356, oxygen sensor 4358, analyte sensor 4360, moisture sensor 4362, LiDAR sensor 4364, or any combination thereof. Typically, each of one or more sensors or transducers 4270 is configured to output sensor data received and stored in a memory device.
尽管一个或多个换能器4270被示出和描述为包括压力传感器4272、流量传感器4274、电动机速度传感器4276和音频传感器4278中的每一者，但是如上所述的其他传感器可以包括本文描述和/或示出的传感器中的每一个的任何组合和任何数量。Although one or more transducers 4270 are shown and described as including each of pressure sensor 4272, flow sensor 4274, motor speed sensor 4276, and audio sensor 4278, other sensors as described above may include those described herein and /or any combination and any number of each of the sensors shown.
一个或多个传感器4270可用于生成传感器数据，诸如图像数据、音频数据、测距数据、轮廓映射数据、热数据、生理数据、环境数据等。该传感器数据可以由控制系统使用以确定用户接口并识别与用户接口100的当前适配性相关联的特性。One or more sensors 4270 may be used to generate sensor data such as image data, audio data, odometry data, contour mapping data, thermal data, physiological data, environmental data, etc. This sensor data may be used by the control system to determine the user interface and identify characteristics associated with the current suitability of the user interface 100 .
示例压力传感器4272是生成指示图1中的呼吸治疗系统的用户的呼吸(例如，吸入和/或呼出)和/或环境压力的传感器数据的空气压力传感器(例如，大气压力传感器)。在此类实施方式中，该压力传感器4272可以联接到RPT装置40或集成在RPT装置40中。压力传感器4272可以是例如，电容传感器、电磁传感器、压电传感器、应变仪传感器、光学传感器、电位传感器或其任何组合。Example pressure sensor 4272 is an air pressure sensor (eg, barometric pressure sensor) that generates sensor data indicative of the breathing (eg, inhalation and/or exhalation) and/or ambient pressure of the user of the respiratory therapy system in FIG. 1 . In such implementations, the pressure sensor 4272 may be coupled to or integrated into the RPT device 40 . Pressure sensor 4272 may be, for example, a capacitive sensor, an electromagnetic sensor, a piezoelectric sensor, a strain gauge sensor, an optical sensor, a potentiometric sensor, or any combination thereof.
在WO 2012/012835中描述了流量传感器(例如流量传感器4274)的实例，该专利在此通过引用整体并入本文。在一些实施方式中，流量传感器4274用于确定来自RPT装置40的空气流速、通过空气回路4170的导管的空气流速、通过用户接口100的空气流速，或其任何组合。在此类实施方式中，流量传感器4274可以联接到RPT装置40、用户接口100或将用户接口100附接到RPT装置40的导管或者集成在RPT装置40、用户接口100或将用户接口100附接到RPT装置40的导管中。流量传感器4274可以是质量流量传感器，诸如旋转流量计(例如，霍尔效应流量计)、涡轮流量计、孔板流量计、超声流量计、热线传感器、涡流传感器、膜传感器或其任何组合。在一些实施方式中，流量传感器4274被配置成测量通气口流量(例如，有意“泄漏”)、无意泄漏(例如，嘴泄漏和/或面罩泄漏)、用户流量(例如，进入和/或离开肺的空气)或其任何组合。在一些实施方式中，可以分析流速数据以确定用户的心原性振荡。Examples of flow sensors (eg flow sensor 4274) are described in WO 2012/012835, which is hereby incorporated by reference in its entirety. In some embodiments, the flow sensor 4274 is used to determine the air flow rate from the RPT device 40, the air flow rate through the conduit of the air circuit 4170, the air flow rate through the user interface 100, or any combination thereof. In such embodiments, the flow sensor 4274 may be coupled to or integrated with the RPT device 40 , the user interface 100 , or the catheter that attaches the user interface 100 to the RPT device 40 . into the catheter of the RPT device 40. Flow sensor 4274 may be a mass flow sensor such as a rotational flow meter (eg, Hall effect flow meter), turbine flow meter, orifice flow meter, ultrasonic flow meter, hot wire sensor, eddy current sensor, membrane sensor, or any combination thereof. In some embodiments, flow sensor 4274 is configured to measure vent flow (e.g., intentional "leak"), unintentional leakage (e.g., mouth leak and/or mask leak), user flow (e.g., into and/or out of the lungs) air) or any combination thereof. In some embodiments, flow rate data can be analyzed to determine the user's cardiogenic oscillations.
在一些实施方式中，温度传感器4330生成指示以下的温度数据：用户10的核心体温、用户的局部或平均皮肤温度、从RPT装置40流动且/或通过导管的空气的局部或平均温度、用户接口100中的局部或平均温度、环境温度或其任何组合。温度传感器4330可以是例如热电偶传感器、热敏电阻传感器、硅带隙温度传感器或基于半导体的传感器、电阻温度检测器或其任何组合。在一些情况下，该温度传感器是非接触式温度传感器，诸如红外高温计。In some embodiments, the temperature sensor 4330 generates temperature data indicative of: the user's 10 core body temperature, the user's local or average skin temperature, the local or average temperature of the air flowing from the RPT device 40 and/or through the conduit, the user interface Local or average temperature in 100, ambient temperature, or any combination thereof. Temperature sensor 4330 may be, for example, a thermocouple sensor, a thermistor sensor, a silicon band gap temperature sensor or semiconductor based sensor, a resistance temperature detector, or any combination thereof. In some cases, the temperature sensor is a non-contact temperature sensor, such as an infrared pyrometer.
RF发射器4338生成和/或发射具有预定频率和/或预定幅度(例如，在高频率带内、在低频率带内、长波信号、短波信号等)的无线电波。RF接收器4336检测从RF发射器4338发射的无线电波的反射，并且此数据可以由控制系统分析以确定关于用户10和/或用户接口100的位置信息，和/或本文所述的生理参数中的一个或多个。RF接收器(RF接收器和RF发射器或另一RF对)也可用于外部部件和RPT装置40或其任何组合之间的无线通信。RF接收器4336和RF发射器4338可以组合为RF传感器(例如，RADAR传感器)的一部分。在一些此类实施方式中，RF传感器包括控制电路。RF通信的特定格式可以是WiFi、蓝牙等。The RF transmitter 4338 generates and/or transmits radio waves having a predetermined frequency and/or a predetermined amplitude (eg, in a high frequency band, in a low frequency band, long wave signal, short wave signal, etc.). RF receiver 4336 detects reflections of radio waves emitted from RF transmitter 4338, and this data may be analyzed by the control system to determine location information about user 10 and/or user interface 100, and/or physiological parameters as described herein. one or more of. An RF receiver (RF receiver and RF transmitter or another RF pair) may also be used for wireless communication between external components and RPT device 40 or any combination thereof. RF receiver 4336 and RF transmitter 4338 may be combined as part of an RF sensor (eg, a RADAR sensor). In some such implementations, the RF sensor includes control circuitry. Specific formats for RF communication can be WiFi, Bluetooth, etc.
在一些实施方式中，RF传感器是网格系统的一部分。网格系统的一个实例是WiFi网格系统，该WiFi网格系统可以包括网格节点、网格路由器和网格网关，它们中的每一者可以是移动的/可移动的或固定的。在此类实施方式中，Wi-Fi网格系统包括Wi-Fi路由器和/或Wi-Fi控制器以及一个或多个卫星(例如，接入点)，它们中的每一者包括与RF传感器相同或类似的RF传感器。WiFi路由器和卫星使用WiFi信号持续地与彼此通信。WiFi网格系统可以用于基于路由器与卫星之间的WiFi信号的变化(例如，接收的信号强度的差异)生成运动数据，该WiFi信号的变化是由于移动的物体或人部分地阻塞了信号而引起的。该运动数据可以指示运动、呼吸、心率、步态、跌倒、行为等，或其任何组合。In some embodiments, the RF sensor is part of a grid system. An example of a mesh system is a WiFi mesh system, which may include mesh nodes, mesh routers, and mesh gateways, each of which may be mobile/movable or fixed. In such embodiments, the Wi-Fi mesh system includes a Wi-Fi router and/or a Wi-Fi controller and one or more satellites (e.g., access points), each of which includes an interface with an RF sensor Same or similar RF sensor. WiFi routers and satellites use WiFi signals to continuously communicate with each other. WiFi mesh systems can be used to generate motion data based on changes in the WiFi signal between the router and satellite (e.g., differences in received signal strength) due to moving objects or people partially blocking the signal. caused. This motion data may indicate movement, respiration, heart rate, gait, falls, behavior, etc., or any combination thereof.
来自相机4340的图像数据可由控制系统使用以确定与用户的面部、用户接口100和/或本文所述的生理参数中的一个或多个相关联的信息。例如，来自相机4340的图像数据可用于识别用户的位置、用户面部的一部分的局部颜色、用户接口上的特征相对于用户面部上的特征的相对位置等。在一些实施方式中，该相机包括广角镜头或鱼眼镜头。该相机可以是在可见光谱中操作的相机，诸如在380nm或大约380nm与740nm或大约740nm之间的波长。Image data from camera 4340 may be used by the control system to determine information associated with the user's face, user interface 100, and/or one or more of the physiological parameters described herein. For example, image data from camera 4340 may be used to identify the location of the user, the local color of a portion of the user's face, the relative position of features on the user interface relative to features on the user's face, etc. In some embodiments, the camera includes a wide-angle lens or a fisheye lens. The camera may be a camera operating in the visible spectrum, such as at wavelengths between or about 380 nm and 740 nm or about 740 nm.
IR传感器4342可以是无源传感器或有源传感器。无源IR传感器可以测量来自远处表面的自然红外发射或反射，诸如测量从表面辐射的IR能量以确定该表面的温度。有源IR传感器可以包括生成IR信号的IR发射器，该IR信号然后由IR接收器接收。这种有源IR传感器可用于测量离开物体的IR反射和/或穿过物体的IR发送。例如，作为点投影仪的IR发射器可以使用IR光将可识别的点阵列投影到用户面部上，IR发射器的反射然后可以由IR接收器检测以确定测距数据(例如，与IR传感器4342和远处表面(诸如用户面部的一部分)之间的距离相关联的数据)或与用户面部相关联的轮廓数据(例如与表面相对于该表面的标称高度的相对高度特征相关联的数据)。IR sensor 4342 may be a passive sensor or an active sensor. Passive IR sensors can measure natural infrared emissions or reflections from distant surfaces, such as measuring IR energy radiated from a surface to determine the temperature of the surface. Active IR sensors may include an IR transmitter that generates an IR signal that is then received by an IR receiver. This active IR sensor can be used to measure IR reflections away from an object and/or IR transmission through the object. For example, an IR emitter that is a dot projector can use IR light to project an identifiable array of dots onto a user's face, and the reflections from the IR emitter can then be detected by an IR receiver to determine ranging data (e.g., with IR sensor 4342 data associated with the distance between a distant surface (such as a portion of the user's face) or profile data associated with the user's face (such as data associated with a relative height characteristic of a surface relative to a nominal height of the surface) .
通常，来自IR传感器4342的红外数据可用于确定关于用户10和/或接口100的信息，和/或本文所述的生理参数中的一个或多个。在一个实例中，来自IR传感器的红外数据可用于检测用户面部的一部分或接口100的一部分上的局部温度。IR传感器4342还可与相机结合使用，诸如将IR数据(例如，温度数据或测距数据)与相机数据(例如，局部颜色)关联。IR传感器4342可检测具有在700nm或大约700nm与1mm或大约1mm之间的波长的红外光。Generally, infrared data from IR sensor 4342 may be used to determine information about user 10 and/or interface 100, and/or one or more of the physiological parameters described herein. In one example, infrared data from an IR sensor can be used to detect local temperature on a portion of the user's face or a portion of interface 100 . The IR sensor 4342 may also be used in conjunction with a camera, such as correlating IR data (eg, temperature data or ranging data) with camera data (eg, local color). IR sensor 4342 may detect infrared light having a wavelength between at or about 700 nm and 1 mm at or about 1 mm.
PPG传感器4344输出与用户10相关联的生理数据，该生理数据可以用于确定一个或多个睡眠相关参数，诸如心率、心率可变性、心动周期、呼吸速率、吸气幅度、呼气幅度、吸气-呼气比、估计的血压参数或其任何组合。PPG传感器4344可以由用户佩戴、嵌入在由用户穿着的衣物和/或织物中、嵌入在接口100和/或其相关联的头戴设备(例如，带等)中且/或联接到接口100和/或其相关联的头戴设备(例如，条带等)等。PPG sensor 4344 outputs physiological data associated with user 10 that may be used to determine one or more sleep-related parameters, such as heart rate, heart rate variability, cardiac cycle, respiratory rate, inspiratory amplitude, expiratory amplitude, inhalation Breath-to-expiration ratio, estimated blood pressure parameters, or any combination thereof. PPG sensor 4344 may be worn by a user, embedded in clothing and/or fabric worn by a user, embedded in interface 100 and/or its associated head-mounted device (e.g., strap, etc.), and/or coupled to interface 100 and /or its associated head-mounted device (e.g., strap, etc.), etc.
ECG传感器4346输出与用户10的心脏的电活动相关联的生理数据。在一些实施方式中，ECG传感器4346包括在睡眠时段期间定位在用户10的一部分上或周围的一个或多个电极。来自ECG传感器4346的生理数据可以用于例如，确定本文所述的睡眠相关参数中的一个或多个。ECG sensor 4346 outputs physiological data associated with the electrical activity of the user's 10 heart. In some embodiments, ECG sensor 4346 includes one or more electrodes positioned on or around a portion of user 10 during sleep periods. Physiological data from ECG sensor 4346 may be used, for example, to determine one or more of the sleep-related parameters described herein.
EEG传感器4348输出与用户10的大脑的电活动相关联的生理数据。在一些实施方式中，EEG传感器4348包括在睡眠时段期间定位在用户10的头皮上或周围的一个或多个电极。来自EEG传感器4348的生理数据可以用于例如，在睡眠时段期间的任何给定时间确定用户10的睡眠状态和/或睡眠阶段。在一些实施方式中，EEG传感器4348可以集成在接口100和/或相关联的头戴设备(例如，条带等)中。EEG sensor 4348 outputs physiological data associated with the electrical activity of the user's 10 brain. In some embodiments, EEG sensor 4348 includes one or more electrodes positioned on or around the scalp of user 10 during sleep periods. Physiological data from EEG sensor 4348 may be used, for example, to determine the sleep state and/or sleep stage of user 10 at any given time during a sleep period. In some implementations, EEG sensor 4348 may be integrated into interface 100 and/or an associated headset (eg, a strap, etc.).
EMG传感器4356输出与由一个或多个肌肉产生的电活动相关联的生理数据。氧传感器4358输出指示气体(例如，在导管中或在接口100处)的氧浓度的氧数据。氧传感器4358可以是例如，超声氧传感器、电氧传感器、化学氧传感器、光氧传感器、脉搏血氧计(例如，SpO2传感器)或其任何组合。在一些实施方式中，一个或多个传感器4270还包括皮肤电反应(GSR)传感器、血流量传感器、呼吸传感器、脉搏传感器、血压计传感器、血氧测定传感器或其任何组合。EMG sensor 4356 outputs physiological data associated with electrical activity produced by one or more muscles. Oxygen sensor 4358 outputs oxygen data indicative of the oxygen concentration of the gas (eg, in the conduit or at interface 100). Oxygen sensor 4358 may be, for example, an ultrasonic oxygen sensor, an electrical oxygen sensor, a chemical oxygen sensor, an optical oxygen sensor, a pulse oximeter (eg, Sp02 sensor), or any combination thereof. In some embodiments, one or more sensors 4270 also include galvanic skin response (GSR) sensors, blood flow sensors, respiration sensors, pulse sensors, blood pressure sensors, oximetry sensors, or any combination thereof.
分析物传感器4360可以用于检测诸如用户10的呼气中分析物的存在。由分析物传感器4360输出的数据可以由控制系统使用以确定诸如用户10的呼吸中的任何分析物的身份和浓度。在一些实施方式中，分析物传感器定位在用户10的嘴附近以检测从用户10的嘴呼出的呼吸中的分析物。例如，当接口100是覆盖用户10的鼻和嘴的面罩时，分析物传感器4360可以定位在面罩内以监测用户10的嘴呼吸。在其他实施方式中，诸如当接口100是鼻罩或鼻枕罩时，分析物传感器可以定位在用户10的鼻附近以检测通过鼻呼出的呼吸中的分析物。在其他实施方式中，当接口100是鼻罩或鼻枕罩时，分析物传感器可以定位在嘴附近。在该实施方式中，分析物传感器4360可用于检测是否有任何空气无意中从用户10的嘴泄漏。在一些实施方式中，分析物传感器4360是可用于检测碳基化学品或化合物的挥发性有机化合物(VOC)传感器。在一些实施方式中，分析物传感器4360还可用于检测用户10是通过其鼻还是嘴呼吸。例如，如果由定位在嘴附近或面罩内(在接口100是面罩的实施方式中)的分析物传感器输出的数据检测到分析物的存在，则控制系统可以使用该数据作为用户10正通过其嘴呼吸的指示。Analyte sensor 4360 may be used to detect the presence of an analyte, such as in the exhaled breath of user 10 . The data output by analyte sensor 4360 may be used by the control system to determine the identity and concentration of any analytes such as those in user 10's breath. In some embodiments, an analyte sensor is positioned near the mouth of user 10 to detect analytes in the breath exhaled from the mouth of user 10 . For example, when interface 100 is a mask covering the nose and mouth of user 10, analyte sensor 4360 may be positioned within the mask to monitor mouth breathing of user 10. In other embodiments, such as when interface 100 is a nasal mask or nasal pillow mask, an analyte sensor may be positioned near the nose of user 10 to detect analytes in breath exhaled through the nose. In other embodiments, when interface 100 is a nasal mask or nasal pillow mask, the analyte sensor may be positioned near the mouth. In this embodiment, the analyte sensor 4360 may be used to detect if any air is inadvertently leaking from the user's 10 mouth. In some embodiments, analyte sensor 4360 is a volatile organic compound (VOC) sensor that can be used to detect carbon-based chemicals or compounds. In some embodiments, analyte sensor 4360 may also be used to detect whether user 10 is breathing through his nose or mouth. For example, if data output by an analyte sensor positioned near the mouth or within the mask (in embodiments in which interface 100 is a mask) detects the presence of the analyte, the control system may use that data to indicate that user 10 is passing through his or her mouth. Instructions for breathing.
水分传感器4362可用于检测用户10周围的各个区域(例如，在导管或接口100内部、在用户10面部附近、在导管和接口100之间的连接附近、在导管和RPT装置40之间的连接附近等)中的水分。因此，在一些实施方式中，水分传感器4362可以联接到接口100或集成在接口100或导管中以监测来自RPT装置40的加压空气的湿度。在其他实施方式中，水分传感器4362放置在需要监测水分含量的任何区域附近。水分传感器4362还可以用于监测用户10周围的周围环境例如，卧室内部的空气的湿度。The moisture sensor 4362 may be used to detect various areas around the user 10 (e.g., inside the catheter or interface 100 , near the face of the user 10 , near the connection between the catheter and the interface 100 , near the connection between the catheter and the RPT device 40 etc.). Accordingly, in some embodiments, a moisture sensor 4362 may be coupled to the interface 100 or integrated into the interface 100 or conduit to monitor the humidity of the pressurized air from the RPT device 40 . In other embodiments, moisture sensors 4362 are placed near any area where moisture content needs to be monitored. Moisture sensor 4362 may also be used to monitor the ambient environment around user 10, such as the humidity of the air inside a bedroom.
光检测和测距(LiDAR)传感器4364可用于深度感测。这种类型的光学传感器(例如，激光传感器)可用于检测物体并构建物体(诸如用户面部、接口100或周围环境(例如，生活空间))的三维(3D)图(例如，轮廓图)。LiDAR通常可以利用脉冲激光来进行飞行时间测量。LiDAR也称为3D激光扫描。在使用这种传感器的实例中，具有LiDAR传感器的固定或移动装置(诸如智能电话)可以测量并映射远离传感器延伸5米或更远的区域。例如，LiDAR数据可以与由电磁RADAR传感器估计的点云数据融合。LiDAR传感器还可以使用人工智能(AI)通过检测和分类可能引起RADAR系统的问题的空间中的特征来自动地对RADAR系统建立地理围栏，诸如玻璃窗(该玻璃窗可以是对RADAR高度反射的)。例如，LiDAR还可用于提供人的身高的估计，以及当人坐下或跌倒时身高的变化。LiDAR可用于形成用户面部、用户接口100(例如，当佩戴在用户面部上时)和/或环境的3D网格表示。在进一步的用途中，对于无线电波穿过的固体表面(例如，透射线材料)，LiDAR可以反射离开此类表面，从而允许对不同类型的障碍物进行分类。虽然在本文中描述了LiDAR传感器，但是在一些情况下，可以使用一个或多个其他测距传感器来代替LiDAR传感器或作为LiDAR传感器的补充，诸如超声测距传感器、电磁RADAR传感器等。The Light Detection and Ranging (LiDAR) sensor 4364 can be used for depth sensing. Optical sensors of this type (eg, laser sensors) can be used to detect objects and construct three-dimensional (3D) maps (eg, contour maps) of objects, such as a user's face, the interface 100, or the surrounding environment (eg, a living space). LiDAR typically utilizes pulsed laser light to perform time-of-flight measurements. LiDAR is also known as 3D laser scanning. In an example of using such a sensor, a fixed or mobile device (such as a smartphone) with a LiDAR sensor can measure and map an area extending 5 meters or more away from the sensor. For example, LiDAR data can be fused with point cloud data estimated by electromagnetic RADAR sensors. LiDAR sensors can also use artificial intelligence (AI) to automatically geofence RADAR systems by detecting and classifying features in space that may cause problems for RADAR systems, such as glass windows (which can be highly reflective to RADAR) . For example, LiDAR can also be used to provide an estimate of a person's height and how that height changes when a person sits or falls. LiDAR may be used to form a 3D mesh representation of the user's face, the user interface 100 (eg, when worn on the user's face), and/or the environment. In a further use, for solid surfaces through which radio waves pass (e.g., radiolucent materials), LiDAR can reflect off such surfaces, allowing the classification of different types of obstacles. Although a LiDAR sensor is described herein, in some cases one or more other ranging sensors may be used in place of or in addition to the LiDAR sensor, such as ultrasonic ranging sensors, electromagnetic RADAR sensors, etc.
除了位于RPT装置40、导管或接口100上之外，任何或所有上述传感器可以位于诸如移动用户装置或活动跟踪器的外部装置上。例如，音频传感器4278和扬声器4334集成在移动装置中和/或联接到移动装置，并且压力传感器4272和/或流量传感器4274集成在RPT装置40中和/或联接到RPT装置40。在一些实施方式中，一个或多个传感器中的至少一个在睡眠时段期间可以定位成大体邻近用户10(例如，定位在用户10的一部分上或与用户10的一部分接触、由用户10佩戴、联接到床头柜或定位在床头柜上、联接到床垫、联接到天花板等)。In addition to being located on the RPT device 40, catheter, or interface 100, any or all of the above-described sensors may be located on an external device such as a mobile user device or activity tracker. For example, audio sensor 4278 and speaker 4334 are integrated in and/or coupled to the mobile device, and pressure sensor 4272 and/or flow sensor 4274 are integrated in and/or coupled to RPT device 40. In some embodiments, at least one of the one or more sensors may be positioned generally proximate user 10 during sleep periods (e.g., positioned on or in contact with a portion of user 10 , worn by user 10 , coupled to to or positioned on a bedside table, attached to the mattress, attached to the ceiling, etc.).
在本技术的一种形式中，RPT装置40包括形式为按钮、开关或拨号盘的一个或多个输入装置4220，以允许人与装置进行交互。按钮、开关或拨号盘可以是物理装置，或者是可经由触摸屏幕访问的软件装置。在一种形式中，按钮、开关或拨号盘可以物理连接到外部壳体4010，或者在另一形式中，可以与电连接到中央控制器4230的接收器无线通信。在一种形式中，输入装置4220可以被构造或布置成允许人选择值和/或菜单选项。In one form of the present technology, RPT device 40 includes one or more input devices 4220 in the form of buttons, switches, or dials to allow a human to interact with the device. A button, switch, or dial may be a physical device, or a software device accessible via a touch screen. In one form, a button, switch, or dial may be physically connected to the external housing 4010, or in another form, may communicate wirelessly with a receiver electrically connected to the central controller 4230. In one form, input device 4220 may be constructed or arranged to allow a human to select values and/or menu options.
在本技术的一种形式中，中央控制器4230为一个或多个适于控制RPT装置40的处理器。合适的处理器可包括x86因特尔(INTEL)处理器、基于来自安谋控股公司(ARMHoldings)的处理器的处理器，诸如来自意法半导体公司(STMICROELECTRONIC)的STM32系列微控制器。在本技术的某些替代性形式中，32位RISC CPU，诸如来自意法半导体公司的STR9系列微控制器，或16位RISC CPU，诸如来自由德州仪器公司(TEXAS INSTRUMENTS)制造的MSP430家族微控制器的处理器可同样适用。在本技术的一种形式中，中央控制器4230为专用电子回路。在一种形式中，中央控制器4230为专用集成电路。在另一形式中，中央控制器4230包括分立电子部件。中央控制器4230可被配置成接收来自一个或多个换能器4270、一个或多个输入装置4220以及加湿器60的输入信号。In one form of the present technology, central controller 4230 is one or more processors adapted to control RPT device 40. Suitable processors may include x86 Intel (INTEL) processors, based on A processor of a processor, such as the STM32 series of microcontrollers from STMICROELECTRONIC. In some alternative forms of this technology, a 32-bit RISC CPU, such as the STR9 series of microcontrollers from STMicroelectronics, or a 16-bit RISC CPU, such as from the MSP430 family of microcontrollers manufactured by Texas Instruments The controller's processor may be equally applicable. In one form of the present technology, the central controller 4230 is a dedicated electronic circuit. In one form, central controller 4230 is an application specific integrated circuit. In another form, central controller 4230 includes discrete electronic components. Central controller 4230 may be configured to receive input signals from one or more transducers 4270 , one or more input devices 4220 , and humidifier 60 .
中央控制器4230可被配置成向输出装置4290、治疗装置控制器4240、数据通信接口4280和加湿器60中的一者或多者提供输出信号。Central controller 4230 may be configured to provide output signals to one or more of output device 4290, treatment device controller 4240, data communications interface 4280, and humidifier 60.
在本技术的一些形式中，中央控制器4230被配置成实施本文描述的一种或多种方法，诸如一种或多种表示为存储在内部存储器上的非暂时性计算机可读存储介质中的计算机程序的算法。在本技术的一些形式中，中央控制器4230可与RPT装置40集成。然而，在本技术的一些形式中，一些方法可通过远程定位装置，诸如移动计算装置来执行。例如，远程定位装置可通过分析诸如来自本文所述的任何传感器的存储数据来确定呼吸机的控制设置或检测呼吸相关事件。如上解释，外部源或中央控制器4230的所有数据和操作的所有权通常归属于RPT装置40的制造商。因此，来自传感器的数据和任何其他附加操作数据通常不能由任何其他装置访问。In some forms of the technology, central controller 4230 is configured to implement one or more methods described herein, such as one or more representations stored in a non-transitory computer-readable storage medium on internal memory. Algorithms for computer programs. In some forms of the present technology, central controller 4230 may be integrated with RPT device 40. However, in some forms of the technology, some methods may be performed by a remotely located device, such as a mobile computing device. For example, a remotely located device may determine the ventilator's control settings or detect breathing-related events by analyzing stored data, such as from any of the sensors described herein. As explained above, ownership of all data and operations of the external source or central controller 4230 generally resides with the manufacturer of the RPT device 40. Therefore, the data from the sensor and any other additional operational data generally cannot be accessed by any other device.
在本技术的一种形式中，提供了数据通信接口，并且该数据通信接口连接到中央控制器4230。数据通信接口可连接到远程外部通信网络和/或本地外部通信网络。远程外部通信网络可以连接到诸如服务器或数据库的远程外部装置。本地外部通信网络可连接到本地外部装置，诸如移动装置或健康监测装置。因此，本地外部通信网络可由RPT装置40或移动装置使用以从其他装置收集数据。In one form of the present technology, a data communication interface is provided and connected to the central controller 4230. The data communication interface can be connected to a remote external communication network and/or a local external communication network. The remote external communication network may be connected to remote external devices such as servers or databases. The local external communication network may be connected to local external devices, such as mobile devices or health monitoring devices. Therefore, the local external communication network can be used by RPT device 40 or mobile devices to collect data from other devices.
在一种形式中，数据通信接口为中央控制器4230的一部分。在另一形式中，数据通信接口4280与中央控制器4230分离，并且可以包括集成电路或处理器。在一种形式中，远程外部通信网络是因特网。数据通信接口可以使用有线通信(例如经由以太网或光纤)或无线协议(例如CDMA、GSM、2G、3G、4G/LTE、LTE Cat-M、NB-IoT、5G新空口、卫星、超越5G)连接到因特网。在一种形式中，本地外部通信网络4284利用一种或多种通信标准，诸如蓝牙或消费者红外协议。In one form, the data communications interface is part of the central controller 4230. In another form, data communications interface 4280 is separate from central controller 4230 and may include an integrated circuit or processor. In one form, the remote external communications network is the Internet. The data communications interface may use wired communications (e.g. via Ethernet or fiber optics) or wireless protocols (e.g. CDMA, GSM, 2G, 3G, 4G/LTE, LTE Cat-M, NB-IoT, 5G New Radio, Satellite, Beyond 5G) Connect to the Internet. In one form, local external communication network 4284 utilizes one or more communication standards, such as Bluetooth or Consumer Infrared Protocol.
示例RPT装置40包括如图4C中示出的集成传感器和通信电子设备。较老的RPT装置可以用传感器模块来翻新，该传感器模块可以包括用于发送收集的数据的通信电子设备。这种传感器模块可以附接到RPT装置，并且从而将操作数据发送到服务器210中的远程分析引擎。Example RPT device 40 includes integrated sensor and communication electronics as shown in Figure 4C. Older RPT units can be retrofitted with sensor modules that can include communications electronics for sending collected data. Such sensor modules may be attached to the RPT device and thereby send operational data to a remote analytics engine in server 210.
图5示出了将RPT装置40连接到图1中的接口100的空气回路4170中的音频传感器4278的图。在该实例中，(长度为L的)导管180有效地用作由RPT装置40产生的声音的声学波导。在该实例中，输入信号是由RPT装置40发射的声音。输入信号(例如，脉冲)进入定位在导管180一端的音频传感器4278，在导管180中沿空气路径传播到面罩100，并被空气路径(其包括导管180和面罩100)中的特征沿导管180反射回来，以再次进入音频传感器4278。因此，系统IRF(由输入脉冲产生的输出信号)含有输入信号分量和反射分量。一个关键特征是声音从空气路径的一端传播到相对端花费的时间。该间隔在系统IRF中显示，因为音频传感器4278接收来自RPT装置40的输入信号，然后在一段时间之后接收输入信号，该输入信号由导管180过滤，并由面罩100(以及可能地附接到面罩的任何其他系统190，例如当面罩100固定在用户身上时的人呼吸系统)反射和过滤。这意味着与来自导管180的面罩端的反射相关联的系统IRF的分量(反射分量)相对于与输入信号相关联的系统IRF的分量(输入信号分量)被延迟，该输入信号在相对短暂的延迟之后到达音频传感器4278。(为了实际目的，可以忽略此短暂的延迟，并且当麦克风首先响应于输入信号时时间近似为零。)该延迟等于2L/c(其中L是导管的长度，并且c是导管中声音的速度)。FIG. 5 shows a diagram of the audio sensor 4278 in the air circuit 4170 connecting the RPT device 40 to the interface 100 in FIG. 1 . In this example, conduit 180 (of length L) effectively serves as an acoustic waveguide for the sound produced by RPT device 40 . In this example, the input signal is sound emitted by RPT device 40. Input signals (e.g., pulses) enter audio sensor 4278 positioned at one end of conduit 180 , propagate along an air path in conduit 180 to mask 100 , and are reflected along conduit 180 by features in the air path (which includes conduit 180 and mask 100 ). Come back to enter Audio Sensor 4278 again. Therefore, the system IRF (output signal generated by the input pulse) contains input signal components and reflected components. A key characteristic is the time it takes for sound to travel from one end of the air path to the opposite end. This interval is shown in the system IRF because the audio sensor 4278 receives an input signal from the RPT device 40 and then, some time later, an input signal that is filtered by the conduit 180 and passed by the mask 100 (and possibly attached to the mask any other system 190, such as the human respiratory system when the mask 100 is secured to the user) reflection and filtering. This means that the component of the system IRF associated with reflections from the mask end of conduit 180 (reflected component) is delayed relative to the component of the system IRF associated with the input signal (input signal component) which occurs within a relatively brief delay Afterwards audio sensor 4278 is reached. (For practical purposes, this short delay can be ignored, and the time is approximately zero when the microphone first responds to the input signal.) This delay is equal to 2L/c (where L is the length of the conduit, and c is the speed of sound in the conduit) .
另一特征是，由于空气路径易于损失，如果导管足够长，则输入信号分量在系统IRF的反射分量已经开始时衰减到可忽略的量。如果是这种情况，则输入信号分量可以与系统IRF的反射分量分离。或者，输入信号可以源自在空气路径的装置端的扬声器。Another feature is that, since the air path is prone to losses, if the conduit is long enough, the input signal component attenuates to a negligible amount when the reflected component of the system IRF has already begun. If this is the case, the input signal component can be separated from the reflected component of the system IRF. Alternatively, the input signal may originate from a speaker at the device end of the air path.
公开的声学分析技术的一些实施方式可以实施倒谱分析。倒谱可以认为是分贝频谱的正向傅立叶变换的对数频谱的傅立叶逆变换等。该操作基本上可以将脉冲响应函数(IRF)和声源的卷积转换为加法操作，使得然后可以更容易地考虑或去除声源，以便分离IRF的数据用于分析。倒谱分析的技术详细描述于题为“倒谱：处理指南(The Cepstrum:AGuide to Processing)”(Childers等人,《电气与电子工程师协会会报(Proceedings ofthe IEEE)》，第65卷，第10期，1977年10月)的科学论文和Randall RB，《频率分析(Frequency Analysis)》，哥本哈根：Bruel&Kjaer出版社，第344页(1977年，修订版1987年)。倒谱分析在呼吸治疗系统部件识别中的应用详细描述于题为“用于呼吸治疗设备的声学检测(Acoustic Detection for Respiratory Treatment Apparatus)”的PCT公布第WO2010/091462号，该专利的全部内容在此通过引用并入。Some embodiments of the disclosed acoustic analysis techniques may implement cepstral analysis. The cepstrum can be thought of as the forward Fourier transform of the decibel spectrum, the inverse Fourier transform of the logarithmic spectrum, etc. This operation essentially turns the convolution of an impulse response function (IRF) and a sound source into an additive operation, making it easier to then account for or remove the sound source in order to separate the IRF's data for analysis. The technique of cepstrum analysis is described in detail in "The Cepstrum: AGuide to Processing" (Childers et al., Proceedings of the IEEE, Vol. 65, no. 10, October 1977) and Randall RB, Frequency Analysis, Copenhagen: Bruel & Kjaer, p. 344 (1977, revised edition 1987). The application of cepstrum analysis to the identification of respiratory therapy system components is described in detail in PCT Publication No. WO2010/091462 entitled "Acoustic Detection for Respiratory Treatment Apparatus", the entire contents of which are at This is incorporated by reference.
如前提及的，呼吸治疗系统通常包括呼吸治疗装置(例如，RPT装置)、加湿器、空气递送导管和患者接口，诸如图1中示出的那些部件。多种不同形式的患者接口可以与给定的RPT装置一起使用，例如鼻枕、鼻叉管、在鼻脊上密封的鼻罩、在鼻的下周边处密封而不是在鼻脊上密封的仅鼻罩、以传统的全面部罩的方式在鼻梁上密封或者在鼻的下周边处密封而不是在鼻脊上密封的鼻和嘴(口鼻)面罩、管向下面罩(其中导管连接到面罩的面向前的部分)、具有导管头戴设备的面罩，具有与主导管连接的集成短管的面罩，以及具有诸如弯头的脱离联接结构的面罩，其中主导管直接连接到该弯头以及其他类型的面罩和上述变型。此外，可以使用不同形式的空气递送导管。为了提供对递送到用户接口的治疗的改善的控制，可以分析测量或估计治疗参数，诸如用户接口中的压力和通气口流量。在较老的系统中，可以确定由用户使用的部件类型的知识，如下面将解释的，以确定用户的最佳接口。一些RPT装置包括菜单系统，该菜单系统允许用户选择使用的系统部件(包括用户接口)的类型，例如品牌、形式、型号等。一旦用户输入了部件的类型，RPT装置就可以选择与选择的部件最佳协调的流量发生器的合适的操作参数。由RPT装置收集的数据可用于评估诸如用户接口的特定选择的部件在向用户供应加压空气时的有效性。As mentioned previously, respiratory therapy systems typically include a respiratory therapy device (eg, an RPT device), a humidifier, an air delivery conduit, and a patient interface, such as those shown in Figure 1 . Many different forms of patient interfaces can be used with a given RPT device, such as nasal pillows, nasal furcation tubes, nasal masks that seal on the nasal ridge, only ones that seal at the lower perimeter of the nose rather than on the nasal ridge. Nasal mask, nose and mouth (oronasal) mask that seals on the bridge of the nose in the manner of a traditional full face mask or seals at the lower perimeter of the nose rather than on the nasal ridge, tube-down mask (where tubes are connected to the mask forward-facing portion), masks with catheter headsets, masks with integrated short tubes connected to the main tube, and masks with breakaway coupling structures such as elbows to which the main tube is directly connected, and others Types of masks and the above variants. Additionally, different forms of air delivery conduits may be used. To provide improved control of the therapy delivered to the user interface, therapy parameters such as pressure and vent flow in the user interface may be analytically measured or estimated. In older systems, knowledge of the types of components used by the user can be determined, as will be explained below, to determine the best interface for the user. Some RPT devices include a menu system that allows the user to select the type of system component (including user interface) to use, such as make, form, model, etc. Once the user enters the type of component, the RPT device can select the appropriate operating parameters of the flow generator that best coordinate with the selected component. The data collected by the RPT device can be used to evaluate the effectiveness of specifically selected components, such as the user interface, in supplying pressurized air to the user.
声学分析可用于识别呼吸压力治疗系统的部件，如上面参考图5解释的。在本说明书中，部件的“识别”是指该部件的类型的识别。在下文中，为了简洁起见，“面罩”与“用户接口”同义使用，即使存在通常未被描述为“面罩”的用户接口。Acoustic analysis can be used to identify components of the respiratory pressure therapy system, as explained above with reference to Figure 5. In this specification, "identification" of a component means identification of the type of the component. In the following, for the sake of brevity, "mask" is used synonymously with "user interface" even if there are user interfaces that are not typically described as "mask".
该系统可以经由分析由音频传感器4278获取的声音信号来识别使用中的导管的长度以及连接到导管的面罩。该技术可以识别面罩和导管，而不管用户在识别时是否佩戴面罩。The system can identify the length of the catheter in use and the mask connected to the catheter via analysis of the acoustic signal acquired by the audio sensor 4278. The technology can identify masks and catheters regardless of whether the user is wearing a mask at the time of identification.
该技术包括一种分析方法，该分析方法能够将声学面罩反射与其他系统噪声和响应(包括但不限于鼓风机声音)分离。这使得可以识别来自不同面罩的声学反射(通常由面罩形状、配置和材料指示)之间的差异，并且可以允许在没有用户或用户干预的情况下识别不同的面罩。The technology includes an analysis method that is able to separate acoustic mask reflections from other system noise and responses, including but not limited to blower sound. This makes it possible to identify differences between acoustic reflections from different masks (often indicated by mask shape, configuration and material) and can allow identification of different masks without user or user intervention.
识别面罩的一示例方法是以至少奈奎斯特速率(例如20kHz)对由音频传感器4278获取的输出声音信号y(t)进行采样，根据采样的输出信号计算倒谱，然后将倒谱的反射分量与倒谱的输入信号分量分离。倒谱的反射分量包括来自输入声音信号的面罩的声学反射，并且因此被称为面罩的“声学特征标记”或“面罩特征标记”。然后将声学特征标记与从含有已知面罩的系统获得的先前测量的声学特征标记的预定义或预定数据库进行比较。可选地，将设置一些标准以确定合适的类似性。在一个示例实施例中，可以基于测量的和存储的声学特征标记之间的互相关中的单个最大数据峰值来完成这些比较。然而，可以通过在数个数据峰值上进行比较来改善该方法，或者替代地，其中比较在提取的独特的倒谱特征集合上完成。An example method of identifying a mask is to sample the output sound signal y(t) acquired by the audio sensor 4278 at at least the Nyquist rate (e.g., 20 kHz), calculate the cepstrum based on the sampled output signal, and then add the reflection of the cepstrum components are separated from the input signal components of the cepstrum. The reflection component of the cepstrum includes the acoustic reflections from the mask of the input sound signal, and is therefore known as the "acoustic signature" or "mask signature" of the mask. The acoustic signature is then compared to a predefined or predetermined database of previously measured acoustic signatures obtained from systems containing known masks. Optionally, some criteria will be set to determine appropriate similarities. In one example embodiment, these comparisons may be accomplished based on the single largest data peak in the cross-correlation between measured and stored acoustic signatures. However, the method can be improved by making comparisons over several data peaks, or alternatively, where the comparison is done on a unique set of extracted cepstral features.
或者，通过找到从RPT装置40接收的声音与其来自正在接收的面罩100的反射之间的延迟，也可以使用相同的方法来确定导管长度；该延迟可以与管180的长度成比例。另外，管直径的变化可以增加或减少反射信号的振幅，因此也可以是可识别的。这种评估可以通过将当前反射数据与先前反射数据进行比较来进行。直径变化可以被认为是来自反射信号(即，反射数据)的幅度变化的比例。Alternatively, the same method can be used to determine conduit length by finding the delay between the sound received from the RPT device 40 and its reflection from the receiving mask 100; this delay can be proportional to the length of the tube 180. Additionally, changes in tube diameter can increase or decrease the amplitude of the reflected signal and therefore can also be discernible. This evaluation can be performed by comparing current reflection data with previous reflection data. The diameter change can be thought of as the proportion of the amplitude change from the reflected signal (i.e., the reflected data).
根据本技术，然后可以将与反射分量相关联的数据与来自先前识别的面罩反射分量(诸如面罩反射分量的存储器或数据库中含有的面罩反射分量)的类似数据进行比较。According to the present technique, data associated with the reflection component may then be compared to similar data from a previously identified mask reflection component, such as a mask reflection component contained in a memory or database of mask reflection components.
例如，经测试的面罩的反射分量(“面罩特征标记”)可以与由麦克风生成的输出信号的倒谱分离。该面罩特征标记可以与作为设备的数据模板存储的已知面罩的先前或预定面罩特征标记的面罩特征标记进行比较。这样做的一种方式是为所有已知的面罩或数据模板计算经测试的面罩的面罩特征标记和先前存储的面罩特征标记之间的互相关系。具有最高峰值的互相关对应于经测试的面罩的概率很高，并且峰值的位置应该与管道的长度成比例。For example, the reflected component of the tested mask ("mask signature") can be separated from the cepstrum of the output signal generated by the microphone. The mask signature may be compared to a mask signature of a previous or predetermined mask signature of a known mask stored as a data template for the device. One way of doing this is to compute the correlation between the mask signature of the tested mask and the previously stored mask signature for all known masks or data templates. The cross-correlation with the highest peak corresponds to the tested mask with a high probability, and the location of the peak should be proportional to the length of the tube.
如上解释，RPT装置40可以提供用户接口类型的数据以及操作数据。该操作数据可以与面罩类型和与用户相关的数据关联，以确定特定面罩类型是否有效。例如，该操作数据反映RPT装置40的使用时间以及该使用是否提供有效治疗。用户接口的类型可以与如根据由RPT装置40收集的操作数据确定的用户依从性或治疗有效性的程度关联。相关数据可用于更好地为需要来自类似RPT装置的呼吸治疗的新用户确定有效接口。该选择可以与从新用户的面部扫描获得的面部维度相结合，以帮助选择接口。As explained above, the RPT device 40 may provide user interface type data as well as operational data. This operational data can be correlated with mask type and user-related data to determine whether a particular mask type is effective. For example, the operational data reflects how long the RPT device 40 has been used and whether that use provided effective treatment. The type of user interface may be associated with the degree of user compliance or treatment effectiveness as determined from operational data collected by the RPT device 40 . Related data can be used to better identify effective interfaces for new users requiring respiratory therapy from similar RPT devices. This selection can be combined with facial dimensions obtained from facial scans of new users to aid in interface selection.
因此，本技术的实例可以允许用户通过将从RPT装置的使用采集的与用户群体的不同面罩有关的数据与由扫描过程确定的个体用户的面部特征进行整合来更快且方便地获得诸如面罩的用户接口。该扫描过程允许用户在自己家中使用计算装置(诸如台式计算机、平板电脑、智能电话或其他移动装置)舒适地快速测量他们的面部解剖结构。然后，在使用各种不同接口分析用户的面部维度和来自一般用户群体的数据之后，计算装置可以接收或生成适当用户接口尺寸和类型的推荐。Accordingly, examples of the present technology may allow users to more quickly and conveniently obtain masks, such as masks, by integrating data collected from the use of the RPT device regarding different masks for a population of users with the facial characteristics of individual users as determined by the scanning process. User interface. This scanning process allows users to quickly measure their facial anatomy from the comfort of their own home using a computing device such as a desktop computer, tablet, smartphone, or other mobile device. The computing device can then receive or generate recommendations for appropriate user interface sizes and types after analyzing the user's facial dimensions and data from the general user population using various different interfaces.
在有益的实施例中，本技术可以采用可从制造商或第三方服务器下载到具有集成相机的智能电话或平板电脑的应用程序。当启动时，该应用程序可以提供视觉和/或音频指令。按照指导，用户(即用户)可以站在镜子前面，并按下用户接口上的相机按钮。然后，激活的过程可以拍摄用户面部的一系列照片，并且然后在例如数秒内获得面部维度以选择接口(基于分析照片的处理器)。In advantageous embodiments, the present technology may employ an application downloadable from the manufacturer or third-party server to a smartphone or tablet with an integrated camera. When launched, the application can provide visual and/or audio instructions. Following the instructions, the user (i.e. the user) can stand in front of the mirror and press the camera button on the user interface. The activated process can then take a series of photos of the user's face, and then obtain the facial dimensions to select an interface (based on a processor analyzing the photos) within, for example, seconds.
用户/用户可以捕捉他们的面部解剖结构的一个图像或一系列图像。一个实例可以是由存储在计算机可读介质上的应用程序提供的指令，诸如当由处理器执行时，检测图像内的各种面部界标，测量并缩放此类界标之间的距离，将这些距离与数据记录进行比较，以及推荐适当的用户接口尺寸。因此，消费者的自动化装置可以允许诸如在家中进行准确的用户接口选择，以允许客户在没有训练过的同事的情况下确定尺寸制定。The user/user can capture an image or a series of images of their facial anatomy. One example may be instructions provided by an application stored on a computer-readable medium, such as, when executed by a processor, detecting various facial landmarks within an image, measuring and scaling distances between such landmarks, converting such distances Compare with data records and recommend appropriate user interface dimensions. Thus, consumer automation devices may allow for accurate user interface selection, such as at home, allowing customers to determine sizing without a trained colleague.
其他实例可以包括从图像中识别三维面部特征。面部特征的识别是基于不同特征的“形状”来制定尺寸的。该形状被描述为用户面部的近乎连续的表面。实际上，连续表面是不可能的，但是在面部上收集大约10k至100k个点提供了面部的连续表面的近似。存在用于收集面部图像数据以识别三维面部特征的数种示例技术。Other examples could include identifying three-dimensional facial features from images. Recognition of facial features is sized based on the "shape" of the different features. The shape is described as a nearly continuous surface of the user's face. In reality, a continuous surface is not possible, but collecting about 10k to 100k points on the face provides an approximation of a continuous surface of the face. Several example techniques exist for collecting facial image data to identify three-dimensional facial features.
一种方法可以是根据2D图像确定面部图像。在该方法中，采用计算机视觉(CV)和训练过的机器学习(ML)模型来提取关键面部标志。例如，OpenCV和DLib库可以通过具有训练数量的标准面部界标来用于标志比较。一旦初步面部标志被提取，导出的三维特征必须适当地缩放。缩放涉及确定诸如硬币、信用卡或用户虹膜的物体以提供已知的缩放。例如，谷歌(Google)Mediapipe Facemesh和虹膜(Iris)模型可以跟踪用户的虹膜并且为了面罩尺寸制定的目的而缩放面部标志。这些模型含有468个面部标志和10个眼睛标志。然后使用虹膜数据来缩放其他识别的面部特征。One approach could be to determine the facial image based on the 2D image. In this method, computer vision (CV) and trained machine learning (ML) models are employed to extract key facial landmarks. For example, the OpenCV and DLib libraries can be used for landmark comparison by having a training population of standard facial landmarks. Once preliminary facial landmarks are extracted, the derived 3D features must be scaled appropriately. Zooming involves locating objects such as coins, credit cards, or the user's iris to provide a known zoom. For example, the Google Mediapipe Facemesh and Iris models can track a user's irises and scale facial landmarks for mask sizing purposes. These models contain 468 facial landmarks and 10 eye landmarks. The iris data is then used to scale other recognized facial features.
确定三维特征的另一方法可以来自从具有深度传感器的3D相机获得的面部数据。3D相机(诸如iPhone X及以上型号上的相机)可以执行面部的3D扫描并返回网格化(三角)表面。表面点的数量通常为约50k。在该实例中，存在来自诸如iPhone的3D相机的2种类型的输出。这些是：(a)原始扫描数据，以及(b)用于面部检测和跟踪的较低分辨率混合形状模型。后者包括自动标志处理，而前者不包括自动标志处理。网格表面数据不需要缩放。Another method of determining three-dimensional features can come from facial data obtained from a 3D camera with a depth sensor. A 3D camera (such as the one on iPhone X and above) can perform a 3D scan of the face and return a meshed (triangulated) surface. The number of surface points is typically around 50k. In this instance, there are 2 types of output from a 3D camera such as an iPhone. These are: (a) raw scan data, and (b) lower resolution hybrid shape models for face detection and tracking. The latter includes automatic flag handling, while the former does not. Mesh surface data does not require scaling.
另一方法是根据2D图像直接生成3D模型。这涉及使用3D形变模型(或3DMM)和机器学习来调整3DMM的形状以匹配图像中的面部。单个或多个图像视图可以来自多个角度，并且可以从捕捉在数字相机上的视频中导出。3DMM可以适于经由机器学习匹配例程来匹配从多个2D图像中获得的数据。3DMM可适于说明面部图像中示出的形状、姿势和表情来修改面部特征。仍然可能需要缩放，并且因此对诸如眼睛特征(诸如虹膜)的已知对象的检测和缩放可以用作说明由于诸如年龄的因素引起的缩放误差的参考。Another method is to generate 3D models directly from 2D images. This involves using a 3D deformable model (or 3DMM) and machine learning to adjust the shape of the 3DMM to match the face in the image. Single or multiple image views can be from multiple angles and can be derived from video captured on a digital camera. The 3DMM may be adapted to match data obtained from multiple 2D images via machine learning matching routines. 3DMM can be adapted to account for the shapes, poses and expressions shown in facial images to modify facial features. Scaling may still be required, and therefore detection and scaling of known objects such as eye features (such as iris) can be used as a reference to account for scaling errors due to factors such as age.
三维特征或形状数据可用于面罩尺寸制定。匹配面罩的一种方式是将面部的识别表面与提议的面罩的已知表面对准。然后将这些表面对准。该对准可以通过最近迭代最近点(NICP)技术来执行。然后可以通过确定平均距离来计算适配性得分，该平均距离是面部特征的最近或对应的点与面罩接触表面之间的距离的平均值。低得分对应于良好适配性。Three-dimensional feature or shape data can be used for mask sizing. One way to match a mask is to align the recognition surface of the face with the known surface of the proposed mask. Then align these surfaces. This alignment can be performed by the nearest iterated closest point (NICP) technique. The fit score can then be calculated by determining the average distance, which is the average of the distances between the nearest or corresponding points of the facial feature and the mask contact surface. A low score corresponds to good fit.
面罩尺寸制定的另一方法可以是使用从不同用户收集的3D面部扫描。在该实例中，可以为超过1,000个用户收集3D数据。这些用户根据他们的理想面罩尺寸进行分组。在该实例中，可用的理想面罩尺寸的数量由面罩设计者确定以覆盖不同的用户类型。这种分组方法可以基于其他类型的数据进行分组，诸如根据传统的2D标志进行分组或根据面部形状的主成分进行分组。主成分分析可用于确定面部特征的特性的简化集合。基于面罩尺寸的分组来计算表示每个面罩尺寸的3D面部特征的平均集合。Another approach to mask sizing could be to use 3D facial scans collected from different users. In this instance, 3D data can be collected for over 1,000 users. These users are grouped according to their ideal mask size. In this example, the number of ideal mask sizes available is determined by the mask designer to cover different user types. This grouping method can be based on other types of data, such as grouping based on traditional 2D landmarks or grouping based on principal components of facial shape. Principal component analysis can be used to determine a simplified set of properties of facial features. Grouping based on mask size calculates an average set of 3D facial features representing each mask size.
为了制定新用户的尺寸，进行3D面部扫描或从2D图像中导出3D数据，并且针对平均面部中的每一个计算新用户的适配性得分。选择的面罩尺寸和面罩类型是对应于具有最低适配性得分的平均面部的面罩。可以结合附加的个人偏好。特定面部特征还可以用于基于修改可用的面罩类型中的一种来创建定制的尺寸制定。To sizing a new user, a 3D face scan is performed or 3D data is derived from a 2D image, and the new user's fit score is calculated for each of the average faces. The mask size and mask type selected were those corresponding to the average face with the lowest fit score. Can be combined with additional personal preferences. Specific facial features can also be used to create customized sizing based on modifying one of the available mask types.
图7描绘了可以被实施用于自动面部特征测量和用户接口选择的示例系统200。系统200通常可以包括服务器210、通信网络220和计算装置230中的一者或多者。服务器210和计算装置230可以经由通信网络220通信，通信网络220可以是有线网络222、无线网络224或具有无线链路226的有线网络。在一些版本中，服务器210可以通过向计算装置230提供信息来与计算装置230单向通信，反之亦然。在其他实施例中，服务器210和计算装置230可以共享信息和/或处理任务。例如，可以实施该系统以允许自动购买诸如图1中的面罩100的用户接口，其中该过程可以包括在本文中更详细描述的自动尺寸制定过程。例如，客户可以在运行面罩选择过程之后在线订购面罩，该过程通过结合来自其他面罩的操作数据和来自使用不同类型和尺寸的面罩的患者群体的RPT装置操作数据对客户的面部特征进行图像分析来自动识别合适的面罩尺寸、类型和/或型号。系统200可以包括一个或多个数据库。该一个或多个数据库可以包括患者数据库260、患者接口数据库270和本文描述的任何其他数据库。应当理解，在本技术的一些实例中，系统或方法的执行期间需要访问的所有数据可以存储在单个数据库中。在其他实例中，数据可以存储在两个或更多个单独的数据库中。因此，在这里存在对特定数据库的引用的情况下，应当理解，在一些实例中，特定数据库可以是不同的数据库，而在其他实例中，它可以是较大数据库的一部分。Figure 7 depicts an example system 200 that may be implemented for automated facial feature measurement and user interface selection. System 200 may generally include one or more of server 210 , communication network 220 , and computing device 230 . Server 210 and computing device 230 may communicate via communication network 220 , which may be wired network 222 , wireless network 224 , or a wired network with wireless link 226 . In some versions, server 210 may communicate one-way with computing device 230 by providing information to computing device 230 and vice versa. In other embodiments, server 210 and computing device 230 may share information and/or processing tasks. For example, the system may be implemented to allow automated purchasing of a user interface such as mask 100 in FIG. 1 , where the process may include an automated sizing process described in greater detail herein. For example, a customer can order a face mask online after running a mask selection process that performs image analysis of the customer's facial features by combining operating data from other masks and RPT device operating data from a patient population using different types and sizes of masks. Automatically identifies the appropriate mask size, type and/or model. System 200 may include one or more databases. The one or more databases may include patient database 260, patient interface database 270, and any other database described herein. It will be appreciated that in some examples of the present technology, all data that needs to be accessed during execution of a system or method may be stored in a single database. In other instances, data can be stored in two or more separate databases. Therefore, where there is a reference to a specific database herein, it will be understood that in some instances the specific database may be a different database, while in other instances it may be part of a larger database.
服务器210和/或计算装置230还可以与诸如类似于图1中示出的RPT装置40的RPT装置250的呼吸治疗装置通信。在该实例中，RPT装置250收集与用户使用、面罩泄漏有关的操作数据和其他相关数据，以提供与面罩使用有关的反馈。收集来自RPT装置250的数据，并在用户数据库260中将来自RPT装置250的数据与使用RPT装置250的用户的个体用户数据关联。用户接口数据库270包括关于不同类型和尺寸的接口的数据，诸如可用于新用户的面罩。用户接口数据库270还可以包括每种类型的面罩的声学特征标记数据，该声学特征标记数据可以使得能够根据从呼吸治疗装置收集的音频数据确定面罩类型。由服务器210执行的面罩分析引擎用于根据个体面部维度数据来关联并确定有效面罩尺寸和类型，并且根据由涵盖整个用户群体的RPT装置250收集的操作数据来关联并确定对应的有效性。例如，可以通过检测到的最小泄漏、与治疗计划的最大依从性(例如，面罩开启和关闭时间、开启和关闭事件的频率、使用的治疗压力)、过夜呼吸暂停的次数、AHI水平、在其装置上使用的压力设置以及规定的压力设置来证明有效适配性。该数据可以与面部维度数据或基于新用户的面部图像的其他数据关联。The server 210 and/or the computing device 230 may also communicate with a respiratory therapy device such as an RPT device 250 similar to the RPT device 40 shown in FIG. 1 . In this example, the RPT device 250 collects operational data related to user usage, mask leakage, and other relevant data to provide feedback related to mask use. Data from the RPT device 250 is collected and associated in a user database 260 with individual user data for users using the RPT device 250 . User interface database 270 includes data on different types and sizes of interfaces, such as masks available for new users. The user interface database 270 may also include acoustic signature data for each type of mask, which acoustic signature data may enable determination of the mask type based on audio data collected from the respiratory therapy device. A mask analysis engine executed by the server 210 is used to correlate and determine effective mask sizes and types based on individual facial dimensional data and corresponding effectiveness based on operational data collected by the RPT device 250 covering the entire user population. For example, this can be measured by the smallest leak detected, maximum compliance with the treatment plan (e.g., mask on and off times, frequency of on and off events, treatment pressure used), number of overnight apneas, AHI level, duration of The pressure setting used on the device and the pressure setting specified to demonstrate effective suitability. This data can be associated with facial dimensional data or other data based on the new user's facial image.
例如，可以将从对用户的面部进行成像(诸如3D扫描数据)导出的面部形状与提议的面罩(衬垫、导管、头戴设备)的特征的几何形状进行比较。可以分析形状和几何形状之间的差异以确定是否存在可能导致引发接触区域发红/疼痛的泄漏或高接触压力分区的适配性问题。如本文解释的，为用户群体采集的数据可以与其他形式的数据(诸如检测到的泄漏)组合，以识别用于特定面部形状(即嘴、鼻、脸颊、头等的形状)的最佳面罩系统。For example, the facial shape derived from imaging the user's face (such as 3D scan data) may be compared to the geometry of features of a proposed mask (cushion, catheter, headset). Differences in shape and geometry can be analyzed to determine if there are fit issues that could lead to leaks or high contact pressure partitions that could cause redness/pain in the contact area. As explained herein, data collected for user groups can be combined with other forms of data (such as detected leaks) to identify the best mask system for a specific facial shape (i.e., the shape of the mouth, nose, cheeks, head, etc.) .
如将要解释的，服务器210收集存储在数据库260中的来自多个用户的数据以及存储在数据库270中的对应的面罩尺寸和类型数据，以基于最适配从新用户收集的扫描的面部维度数据的最佳面罩以及为具有类似于新用户的面部维度和其他特征、睡眠行为数据和人口统计数据的用户实现最佳操作数据的面罩来选择适当的面罩。在一些实例中，系统200包括一个或多个数据库，该一个或多个数据库用于存储来自用户群体和由该用户群体使用的对应的多个用户接口的多个面部特征，以及由用户群体使用的具有多个对应的用户接口的呼吸压力治疗装置的操作数据。选择引擎可以联接到该一个或多个数据库，该选择引擎可操作以基于期望的效果并且基于存储的操作数据和用户的面部特征来为用户选择用户接口。该系统200可以被配置成执行选择用户接口的对应的方法。因此，该系统200可以通过确定对于以各种方式类似于新用户的现有用户而言什么样的面罩已被示出是最佳的，向新用户提供面罩推荐。例如，最佳面罩可以是已经示出为与对治疗的最大依从性、最低泄漏、最少呼吸暂停、最低AHI和最积极的主观用户反馈相关联的面罩类型、型号和/或尺寸。在本技术的各种实例中，可以给予这些结果中的每一个在确定最佳面罩方面的影响各种不同的权重。As will be explained, the server 210 collects data from multiple users stored in the database 260 and the corresponding mask size and type data stored in the database 270 to determine the best fit based on the scanned facial dimensional data collected from the new user. Selecting an appropriate mask is based on the optimal mask and the mask that achieves the best operating data for a user with facial dimensions and other characteristics similar to the new user, sleep behavior data, and demographic data. In some examples, system 200 includes one or more databases for storing a plurality of facial features from a population of users and corresponding plurality of user interfaces used by the population of users, and used by the population of users. Operating data of a respiratory pressure therapy device with multiple corresponding user interfaces. A selection engine may be coupled to the one or more databases, the selection engine being operable to select a user interface for the user based on a desired effect and based on stored operational data and the user's facial characteristics. The system 200 may be configured to perform a corresponding method of selecting a user interface. Thus, the system 200 can provide mask recommendations to new users by determining what masks have been shown to be optimal for existing users who are similar to the new user in various ways. For example, the optimal mask may be the mask type, model, and/or size that has been shown to be associated with greatest compliance with treatment, lowest leakage, least apnea, lowest AHI, and most positive subjective user feedback. In various examples of the present technology, various weights may be given to the impact of each of these results in determining the optimal mask.
计算装置230可以是台式或膝上型计算机232或移动装置，诸如智能电话234或平板电脑236。图7描绘了计算装置230的一般架构300。装置230可以包括一个或多个处理器310。装置230还可以包括显示界面320、用户控制/输入界面331、传感器340和/或用于一个或多个传感器的传感器接口、惯性测量单元(IMU)342和非易失性存储器/数据存储装置350。Computing device 230 may be a desktop or laptop computer 232 or a mobile device, such as a smartphone 234 or tablet 236. FIG. 7 depicts a general architecture 300 of a computing device 230. Device 230 may include one or more processors 310. Device 230 may also include a display interface 320, user control/input interface 331, sensors 340 and/or sensor interfaces for one or more sensors, an inertial measurement unit (IMU) 342, and non-volatile memory/data storage 350 .
传感器340可以是集成到计算装置230中的一个或多个相机(例如，CCD电荷耦合装置或有源像素传感器)，诸如在智能电话或膝上型计算机中提供的那些。替代地，在计算装置230是台式计算机的情况下，装置230可以包括用于与诸如图6中描绘的网络摄像头233的外部相机联接的传感器接口。可以与计算装置集成或在计算装置外部的可以用于帮助本文所述的方法的其他示例性传感器包括用于捕捉三维图像的立体相机，或能够检测来自激光器或频闪/结构化光源的反射光的光检测器。Sensor 340 may be one or more cameras (eg, a CCD charge coupled device or an active pixel sensor) integrated into computing device 230, such as those provided in a smartphone or laptop computer. Alternatively, where computing device 230 is a desktop computer, device 230 may include a sensor interface for coupling with an external camera, such as webcam 233 depicted in FIG. 6 . Other exemplary sensors that may be integrated with or external to a computing device that may be used to facilitate the methods described herein include stereo cameras for capturing three-dimensional images, or capable of detecting reflected light from lasers or stroboscopic/structured light sources. of light detectors.
用户控制/输入界面331允许用户提供命令或对于提供给用户的提示或指令的响应。这可以是例如触摸面板、键盘、鼠标、麦克风和/或扬声器。User control/input interface 331 allows the user to provide commands or responses to prompts or instructions provided to the user. This may be, for example, a touch panel, keyboard, mouse, microphone and/or speakers.
显示界面320可以包括监测器、LCD面板等，以显示提示，输出信息(诸如面部测量或接口大小推荐)和其他信息，诸如捕捉显示，如下面进一步详细描述的。Display interface 320 may include a monitor, LCD panel, etc., to display prompts, output information (such as facial measurements or interface size recommendations) and other information, such as capture displays, as described in further detail below.
存储器/数据存储装置350可以是计算装置的内部存储器，诸如RAM、闪存或ROM。在一些实施例中，存储器/数据存储装置350还可以是链接到计算装置230的外部存储器，诸如SD卡、服务器、USB闪存驱动器或光盘。在其他实施例中，存储器/数据存储装置350可以是外部存储器和内部存储器的组合。存储器/数据存储装置350包括存储的数据354和指导处理器310执行某些任务的处理器控制指令352。存储的数据354可以包括由传感器340接收的数据，诸如捕捉的图像，以及作为应用程序的组成部分提供的其他数据。处理器控制指令352也可以作为应用程序的组成部分提供。Memory/data storage 350 may be internal memory of the computing device, such as RAM, flash memory, or ROM. In some embodiments, memory/data storage 350 may also be external memory linked to computing device 230, such as an SD card, server, USB flash drive, or optical disk. In other embodiments, memory/data storage 350 may be a combination of external memory and internal memory. Memory/data storage 350 includes stored data 354 and processor control instructions 352 that direct processor 310 to perform certain tasks. Stored data 354 may include data received by sensors 340, such as captured images, and other data provided as part of the application. Processor control instructions 352 may also be provided as part of the application program.
如上所解释，面部图像可以由诸如智能电话234的移动计算装置捕捉。在计算装置230或服务器210上执行的适当应用程序可以提供三维相关面部数据以帮助选择适当的面罩。该应用程序可以使用任何适当的面部扫描方法。此类应用程序可以包括来自StandardCyborg(https://www.standardcyborg.com/)的Capture、来自Scandy Pro(https://www.scandy.co/products/scandy-pro)的应用程序、来自Qianxun3d(http://www.qianxun3d.com/scanpage)的Beauty3D应用程序、Unre 3D FaceApp(http://www.unre.ai/index.php？route＝ios/detail)，以及来自Bellus3D(https://www.bellus3d.com/)的应用程序。面部扫描的详细过程包括在WO 2017000031中公开的技术，该文献在此通过引用整体并入本文。As explained above, facial images may be captured by a mobile computing device such as smartphone 234. Appropriate applications executing on computing device 230 or server 210 may provide three-dimensional relevant facial data to assist in selecting an appropriate mask. The application can use any suitable facial scanning method. Such applications can include Capture from StandardCyborg (https://www.standardcyborg.com/), applications from Scandy Pro (https://www.scandy.co/products/scandy-pro), applications from Qianxun3d ( Beauty3D application from http://www.qianxun3d.com/scanpage), Unre 3D FaceApp (http://www.unre.ai/index.php?route=ios/detail), and from Bellus3D (https:// www.bellus3d.com/) application. The detailed process of facial scanning includes technology disclosed in WO 2017000031, which is hereby incorporated by reference in its entirety.
一种这样的应用程序是用于面部特征测量和/或用户接口尺寸制定的应用程序360，该应用程序可以是可下载到诸如智能电话234和/或平板电脑236的移动装置的应用程序。可以存储在诸如存储器/数据存储装置350的计算机可读介质上的应用程序360包括编程指令，这些编程指令用于处理器310以执行与面部特征测量和/或用户接口尺寸制定有关的某些任务。该应用程序还包括可以由自动方法的算法处理的数据。此类数据可以包括数据记录、参考特征和校正因子，如下面更详细解释的。One such application is an application for facial feature measurement and/or user interface sizing application 360 , which may be an application downloadable to a mobile device such as a smartphone 234 and/or tablet 236 . Application program 360, which may be stored on a computer-readable medium such as memory/data storage device 350, includes programming instructions for processor 310 to perform certain tasks related to facial feature measurement and/or user interface sizing. . The application also includes data that can be processed by algorithms in automated methods. Such data may include data records, reference characteristics and correction factors, as explained in more detail below.
应用程序360由处理器310执行，以使用二维或三维图像来测量用户面部特征，并基于得到的测量，诸如从一组标准尺寸中选择适当的用户接口尺寸和类型。该方法通常可以表征为包括三个或四个不同的阶段：捕捉前阶段、捕捉阶段、捕捉后图像处理阶段，以及比较和输出阶段。Application 360 is executed by processor 310 to measure user facial features using a two-dimensional or three-dimensional image and select an appropriate user interface size and type based on the resulting measurements, such as from a set of standard sizes. The method can generally be characterized as consisting of three or four distinct stages: a pre-capture stage, a capture stage, a post-capture image processing stage, and a comparison and output stage.
在一些情况下，用于面部特征测量和用户接口尺寸制定的应用程序可以控制处理器310在显示界面320上输出包括参考特征的视觉显示。用户可以诸如通过相机的移动将该特征定位在邻近其面部特征的位置。然后，当满足诸如对准条件的某些条件时，该处理器可以捕捉并存储与参考特征相关联的面部特征的一个或多个图像。这可以在镜子的帮助下完成。镜子将显示的参考特征和用户面部反射到相机。然后，应用程序控制处理器310以识别这些图像内的某些面部特征并测量它们之间的距离。然后，通过图像分析处理，可以使用缩放因子以将面部特征测量(可以是像素计数)转换为基于参考特征的标准面罩测量值。此类值可以是例如标准化的测量单位，诸如米或英寸，以及以此类单位表示的适合于面罩尺寸制定的值。In some cases, an application for facial feature measurement and user interface sizing may control processor 310 to output a visual display on display interface 320 that includes the reference features. The user can position the feature adjacent to his or her facial features, such as through movement of the camera. The processor may then capture and store one or more images of facial features associated with the reference features when certain conditions, such as alignment conditions, are met. This can be done with the help of a mirror. The mirror reflects the displayed reference features and user's face to the camera. The application then controls processor 310 to identify certain facial features within these images and measure distances between them. Then, through the image analysis process, scaling factors can be used to convert facial feature measurements (which can be pixel counts) to standard mask measurements based on reference features. Such values may be, for example, standardized units of measurement such as meters or inches, and values expressed in such units suitable for mask sizing.
可以将附加校正因子应用于这些测量。面部特征测量可以与数据记录进行比较，数据记录包括对应于特定用户接口形式(诸如鼻罩和FFM)的不同用户接口尺寸的测量范围。然后可以基于比较选择推荐的尺寸并作为推荐输出给用户/患者。这个过程可以方便地在任何优选用户位置的舒适范围内实现。应用程序可以在数秒内执行该方法。在一个实例中，该应用程序实时执行该方法。Additional correction factors can be applied to these measurements. Facial feature measurements can be compared to data records including measurement ranges corresponding to different user interface sizes for a particular user interface format, such as nasal mask and FFM. The recommended size can then be selected based on the comparison and output to the user/patient as a recommendation. This process can be conveniently implemented within the comfort of any preferred user position. The application can execute the method within seconds. In one instance, the application executes the method in real time.
在捕捉前阶段，处理器310尤其帮助用户建立用于捕捉一个或多个图像以进行尺寸制定处理的适当的条件。例如，这些条件中的一些包括适当的照明和相机取向以及由握住计算装置230的不稳定的手引起的运动模糊。In the pre-capture phase, the processor 310 assists the user in establishing appropriate conditions for capturing one or more images for sizing processing, among other things. For example, some of these conditions include proper lighting and camera orientation and motion blur caused by unsteady hands holding computing device 230 .
用户可以方便地将用于在诸如计算装置230的用户装置处执行自动测量和尺寸制定的应用程序从诸如第三方应用程序商店服务器的服务器下载到他们的计算装置230上。当下载完成时，这种应用程序可以存储在计算装置的内部非易失性存储器上，诸如RAM或闪存。计算装置230优选地是移动装置，诸如智能电话234或平板电脑236。Users may conveniently download applications for performing automated measurements and sizing at a user device, such as computing device 230, from a server, such as a third-party application store server, onto their computing device 230. When the download is complete, such applications may be stored on the computing device's internal non-volatile memory, such as RAM or flash memory. Computing device 230 is preferably a mobile device, such as a smartphone 234 or tablet 236 .
当用户启动应用程序时，处理器310可以经由显示界面320提示用户提供用户特定信息，诸如年龄、性别、体重和身高。然而，处理器310可以在任何时间提示用户输入该信息，诸如在测量了用户的面部特征之后。处理器310还可以呈现教程，该教程可以可听地和/或可视地呈现(如由应用程序提供的)，以帮助用户理解他们在过程期间的角色。提示还可能需要关于用户接口类型(例如鼻接口或全面部接口等)以及用户接口将用于的装置的类型的信息。而且，在捕捉前阶段，应用程序可以基于已经由用户采集的信息(诸如在接收用户面部的捕捉的图像之后)并且基于机器学习技术或通过人工智能来外推用户特定信息。When the user launches the application, processor 310 may prompt the user via display interface 320 to provide user-specific information, such as age, gender, weight, and height. However, processor 310 may prompt the user to enter this information at any time, such as after measuring the user's facial features. Processor 310 may also present tutorials, which may be audibly and/or visually presented (as provided by the application) to help users understand their role during the process. The prompt may also require information about the type of user interface (eg, nasal interface or full facial interface, etc.) and the type of device the user interface will be used on. Furthermore, in the pre-capture phase, the application may extrapolate user-specific information based on information already collected by the user (such as after receiving a captured image of the user's face) and based on machine learning techniques or through artificial intelligence.
当用户准备继续时(这可以通过用户输入或响应于经由用户控制/输入界面331的提示来指示)，处理器310按照应用程序的处理器控制指令352的指导来激活传感器340。传感器340优选地是移动装置的前向相机，该传感器340位于移动装置的与显示界面320相同的一侧上。该相机通常被配置成捕捉二维图像。捕捉二维图像的移动装置相机是普遍存在的。本技术利用这种普遍存在来避免使用户负担获得专用设备的需要。When the user is ready to proceed (which may be indicated by user input or in response to a prompt via user control/input interface 331 ), processor 310 activates sensor 340 as directed by the application's processor control instructions 352 . Sensor 340 is preferably the forward-facing camera of the mobile device and is located on the same side of the mobile device as display interface 320 . The camera is typically configured to capture two-dimensional images. Mobile device cameras that capture two-dimensional images are ubiquitous. The present technology exploits this ubiquity to avoid burdening users with the need to obtain specialized equipment.
大约在激活传感器/相机340的同时，处理器310按照应用程序的指导在显示界面320上呈现捕捉显示。该捕捉显示可以包括相机实况动作预览、参考特征、目标框以及一个或多个状态指示符或其任何组合。在该实例中，该参考特征以显示界面为中心显示，并且具有对应于显示界面320的宽度的宽度。该参考特征的垂直位置可以使得参考特征的顶部边缘邻接显示界面320的最上部边缘，或者参考特征的底部边缘邻接显示界面320的最下部边缘。显示界面320的一部分将显示相机实况动作预览324，通常在用户处于正确位置和取向时实时地显示由传感器/相机340捕捉的用户面部特征。At approximately the same time as sensor/camera 340 is activated, processor 310 presents a capture display on display interface 320 as directed by the application. The capture display may include a live camera motion preview, reference features, target boxes, and one or more status indicators or any combination thereof. In this example, the reference feature is displayed centered on the display interface and has a width corresponding to the width of the display interface 320 . The vertical position of the reference feature may be such that the top edge of the reference feature abuts the uppermost edge of the display interface 320 or the bottom edge of the reference feature abuts the lowermost edge of the display interface 320 . A portion of the display interface 320 will display a camera live action preview 324, typically showing the user's facial features captured by the sensor/camera 340 in real time when the user is in the correct position and orientation.
该参考特征是计算装置230已知的(预定的)特征，并且向处理器310提供参考框架，该参考框架允许处理器310缩放捕捉的图像。该参考特征优选地可以是不同于用户的面部或解剖特征的特征。因此，在图像处理阶段期间，该参考特征帮助处理器310确定何时满足了某些对准条件，诸如在捕捉前阶段期间。参考特征可以是快速响应(QR)码或已知的样本或标记，其可以向处理器310提供某些信息，诸如缩放信息、取向和/或可以可选地根据QR码的结构确定的任何其他期望的信息。该QR码可以具有正方形或矩形形状。当在显示界面320上显示时，该参考特征具有预定的维度，诸如以毫米或厘米为单位，该参考特征的值可以编码到应用程序中并在适当的时间传送到处理器310。参考特征326的实际维度可以在各种计算装置之间变化。在一些版本中，该应用程序可被配置成特定于计算装置型号，其中当在特定型号上显示时，参考特征326的维度是已知的。然而，在其他实施例中，该应用程序可以指导处理器310从装置230获得某些信息，诸如显示尺寸和/或变焦特性，这些变焦特性允许处理器310计算如经由缩放在显示界面320上显示的参考特征的现实世界/实际维度。无论如何，如在此类计算装置的显示界面320上显示的参考特征的实际维度在捕捉后图像处理之前通常是已知的。The reference feature is a known (predetermined) feature of the computing device 230 and provides the processor 310 with a reference frame that allows the processor 310 to scale the captured image. The reference feature may preferably be a feature different from the user's facial or anatomical features. Therefore, during the image processing stage, this reference feature assists the processor 310 in determining when certain alignment conditions are met, such as during the pre-capture stage. The reference feature may be a Quick Response (QR) code or a known sample or marker, which may provide certain information to the processor 310 such as scaling information, orientation, and/or any other that may optionally be determined based on the structure of the QR code. Desired information. This QR code can have a square or rectangular shape. When displayed on the display interface 320, the reference feature has a predetermined dimension, such as in millimeters or centimeters, and the value of the reference feature can be encoded into the application and communicated to the processor 310 at the appropriate time. The actual dimensions of reference features 326 may vary between various computing devices. In some versions, the application may be configured to be specific to a computing device model, where the dimensions of the reference feature 326 are known when displayed on a particular model. However, in other embodiments, the application may direct the processor 310 to obtain certain information from the device 230 such as display size and/or zoom characteristics that allow the processor 310 to calculate how to display on the display interface 320 via scaling. The real world/actual dimensions of the reference characteristics. Regardless, the actual dimensions of the reference features as displayed on the display interface 320 of such computing devices are typically known prior to post-capture image processing.
与参考特征一起，目标框可以在显示界面320上显示。该目标框允许用户对准目标框中的捕捉显示322内的某些部件，这是成功的图像捕捉所期望的。Together with the reference features, the target frame may be displayed on the display interface 320. The target box allows the user to aim certain components within the capture display 322 in the target box, which is desired for successful image capture.
状态指示符向用户提供关于过程的状态的信息。这有助于确保用户在完成图像捕捉之前不会对传感器/相机的定位进行大的调整。Status indicators provide information to the user about the status of the process. This helps ensure that the user does not make large adjustments to the sensor/camera positioning before completing image capture.
因此，当用户保持显示界面320平行于待测量的面部特征并将用户显示界面320呈现给镜子或其他反射表面时，该参考特征显著地显示并叠加由相机/传感器340看到的并且如由镜子反射的实时图像。该参考特征可以固定在显示界面320的顶部附近。该参考特征以这种方式至少部分地显著地显示，使得传感器340可以清楚地看到参考特征，使得处理器310可以容易地识别特征。此外，该参考特征可以叠加用户面部的实时视图，这有助于避免用户混淆。Therefore, when the user holds the display interface 320 parallel to the facial feature to be measured and presents the user display interface 320 to a mirror or other reflective surface, the reference feature is prominently displayed and superimposed as seen by the camera/sensor 340 and as viewed by the mirror Live image of reflection. This reference feature may be fixed near the top of display interface 320. The reference feature is at least partially prominently displayed in such a manner that the sensor 340 can clearly see the reference feature and the processor 310 can easily identify the feature. Additionally, this reference feature can be overlaid with a live view of the user's face, which helps avoid user confusion.
还可以由处理器310经由显示界面320、由听得见的指令经由计算装置230的扬声器来指导用户，或者由教程提前指导用户将显示界面320定位在待测量的面部特征的面中。例如，可以指导用户定位显示界面320使得它向前面向并且在与待测量的某些面部特征对准的面中放置在用户的下巴之下、抵靠用户的下巴或者邻近用户的下巴。例如，可以将显示界面320放置成与鼻梁点和颏上点平面对准。由于最终捕捉的图像是二维的，所以平面对准有助于确保参考特征326的缩放同样适用于面部特征测量。在这点上，镜子与用户的面部特征和显示器之间的距离将大致相同。The user may also be guided by processor 310 via display interface 320, by audible instructions via speakers of computing device 230, or by a tutorial in advance to position display interface 320 in the face of the facial feature to be measured. For example, the user may be instructed to position display interface 320 so that it faces forward and is placed under, against, or adjacent the user's chin in a plane aligned with certain facial features to be measured. For example, the display interface 320 may be positioned in plane alignment with the bridge of the nose point and the suprasmental point. Since the final captured image is two-dimensional, planar alignment helps ensure that the scaling of reference features 326 is equally applicable to facial feature measurements. At this point, the distance between the mirror and the user's facial features and the display will be approximately the same.
当用户定位在镜子前面，并且包括参考特征的显示界面320被粗略地放置成与待测量的面部特征平面对准时，处理器310检查某些条件以帮助确保充分对准。如前所述，可以由应用程序建立的一个示例性条件是，必须在目标框328内检测到整个参考特征以便继续。如果处理器310检测到参考特征没有完全定位在目标框内，则处理器310可以禁止或延迟图像捕捉。然后，用户可以将他们的面部与显示界面320一起移动，以保持平面性，直到如在实况动作预览中显示的参考特征位于目标框内。这有助于面部特征和显示界面320相对于用于图像捕捉的镜子的优化对准。When the user is positioned in front of a mirror and the display interface 320 including the reference features is positioned roughly in plane alignment with the facial feature to be measured, the processor 310 checks certain conditions to help ensure adequate alignment. As mentioned previously, one example condition that can be established by the application is that the entire reference feature must be detected within target box 328 in order to continue. If the processor 310 detects that the reference feature is not fully positioned within the target box, the processor 310 may inhibit or delay image capture. The user can then move their face with the display interface 320 to maintain planarity until the reference features are within the target box as shown in the live action preview. This facilitates optimal alignment of facial features and display interface 320 relative to the mirror used for image capture.
当处理器310在目标框内检测到整个参考特征时，处理器310可以读取计算装置的IMU 342用于检测装置倾斜角。例如，IMU 342可以包括加速度计或陀螺仪。因此，处理器310可以诸如通过与一个或多个阈值进行比较来评估装置倾斜，以确保装置倾斜在合适的范围内。例如，如果确定计算装置230(以及因此显示界面320和用户的面部特征)在任何方向上倾斜约±5度内，则该过程可以继续到捕捉阶段。在其他实施例中，用于继续的倾斜角可以在约±10度、±7度、±3度或±1度内。如果检测到过度倾斜，则可以显示或发出警告消息以校正不期望的倾斜。这对于帮助用户禁止或减少过度倾斜(特别是在前-后方向上)特别有用，如果不对过度倾斜进行校正，其可能成为测量误差的来源，因为被捕捉的参考图像将不具有适当的纵横比。When the processor 310 detects the entire reference feature within the target frame, the processor 310 may read the IMU 342 of the computing device for detecting the device tilt angle. For example, IMU 342 may include an accelerometer or gyroscope. Accordingly, the processor 310 may evaluate the device tilt, such as by comparing to one or more thresholds, to ensure that the device tilt is within an appropriate range. For example, if it is determined that computing device 230 (and therefore display interface 320 and the user's facial features) is tilted within approximately ±5 degrees in any direction, the process may continue to the capture phase. In other embodiments, the tilt angle for continuation may be within about ±10 degrees, ±7 degrees, ±3 degrees, or ±1 degrees. If excessive tilt is detected, a warning message can be displayed or emitted to correct the undesired tilt. This is particularly useful to help the user inhibit or reduce excessive tilt (especially in the anteroposterior direction), which if not corrected can be a source of measurement error because the reference image being captured will not have the appropriate aspect ratio.
当由如由应用程序控制的处理器310已经确定了对准时，处理器310继续到捕捉阶段。一旦满足对准参数和任何其他先决条件，捕捉阶段优选地自动发生。然而，在一些实施例中，用户可以响应于这样做的提示来发起捕捉。When the alignment has been determined by the processor 310, such as controlled by an application program, the processor 310 proceeds to the capture phase. The capture phase preferably occurs automatically once the alignment parameters and any other prerequisites are met. However, in some embodiments, the user may initiate a capture in response to a prompt to do so.
当发起图像捕捉时，处理器310经由传感器340捕捉n个图像，该n个图像优选地多于一个图像。例如，处理器310经由传感器340可以捕捉约5至20个图像、10至20个图像，或10至15个图像等。捕捉的图像的数量可以是基于时间的。换句话说，捕捉的图像的数量可以基于在预定时间间隔期间可以由传感器340捕捉的预定分辨率的图像的数量。例如，如果传感器340可以在1秒内以预定分辨率捕捉的图像的数量是40个图像，并且用于捕捉的预定时间间隔是1秒，则传感器340将捕捉40个图像用于使用处理器310处理。图像的数量可以是用户定义的、由服务器210基于检测到的环境条件的人工智能或机器学习或基于预期的准确度目标确定。例如，如果需要高准确度，则可能需要更多的捕捉的图像。尽管优选的是捕捉多个图像用于处理，但是也设想了一个图像，并且可以将该一个图像成功地用于获得准确的测量。然而，多于一个图像允许获得平均测量。这可以减少误差/不一致性并提高准确度。处理器310可以将这些图像放置在存储器/数据存储装置350的存储的数据354中，用于捕捉后处理。When image capture is initiated, processor 310 captures n images via sensor 340, the n images preferably being more than one image. For example, processor 310 may capture approximately 5 to 20 images, 10 to 20 images, or 10 to 15 images via sensor 340, etc. The number of images captured can be time-based. In other words, the number of images captured may be based on the number of images at a predetermined resolution that may be captured by the sensor 340 during a predetermined time interval. For example, if the number of images that sensor 340 can capture at a predetermined resolution in 1 second is 40 images, and the predetermined time interval for capturing is 1 second, sensor 340 will capture 40 images for use with processor 310 deal with. The number of images may be user-defined, determined by server 210 based on artificial intelligence or machine learning based on detected environmental conditions or based on expected accuracy goals. For example, if high accuracy is required, more captured images may be needed. Although it is preferred to capture multiple images for processing, one image is also contemplated and can be used successfully to obtain accurate measurements. However, more than one image allows obtaining average measurements. This reduces errors/inconsistencies and increases accuracy. Processor 310 may place these images in stored data 354 of memory/data storage 350 for post-capture processing.
一旦捕捉了图像，处理器310就处理图像以检测或识别面部特征/界标并测量界标之间的距离。得到的测量可用于推荐适当的用户接口尺寸。或者，该处理可以由接收发送的捕捉的图像的服务器210和/或在用户的计算装置(例如，智能电话)上执行。处理也可以由处理器310和服务器210的组合来进行。在一个实例中，推荐的用户接口尺寸可以主要基于用户的鼻宽度。在其他实例中，推荐的用户接口尺寸可以基于用户的嘴和/或鼻维度。Once the image is captured, processor 310 processes the image to detect or identify facial features/landmarks and measure distances between landmarks. The resulting measurements can be used to recommend appropriate user interface dimensions. Alternatively, the processing may be performed by the server 210 that receives the transmitted captured image and/or on the user's computing device (eg, a smartphone). Processing may also be performed by a combination of processor 310 and server 210. In one example, the recommended user interface size may be based primarily on the user's nose width. In other examples, recommended user interface dimensions may be based on the user's mouth and/or nose dimensions.
如由应用程序控制的处理器310从存储的数据354中检索一个或多个捕捉的图像。然后由处理器310提取图像以识别包括二维捕捉的图像的每个像素。然后，处理器310检测像素构成内的某些预先指定的面部特征。The processor 310, as controlled by the application program, retrieves one or more captured images from the stored data 354. The image is then extracted by processor 310 to identify each pixel comprising the two-dimensional captured image. Processor 310 then detects certain pre-specified facial features within the pixel composition.
检测可以由处理器310使用边缘检测来执行，诸如Canny、Prewitt、Sobel或Robert的边缘检测。这些边缘检测技术/算法有助于识别像素构成内的某些面部特征的位置，某些面部特征对应于为图像捕捉而呈现的用户的实际面部特征。例如，边缘检测技术可以首先识别图像内的用户面部，并且还识别图像内对应于特定面部特征的像素位置，这些特定面部特征诸如是每只眼睛及其边界、嘴及其角落、左右鼻翼、鼻梁点、颏上点、眉间点以及左右鼻唇沟等。然后，处理器310可以标记、标注或存储这些特征中的每一者的特定像素位置。替代地，或者如果处理器310/服务器210的这种检测不成功，则可以由人类操作员通过处理器310/服务器210的用户接口查看对捕捉的图像的访问来手动地检测和标记、标注或存储预先指定的面部特征。Detection may be performed by processor 310 using edge detection, such as Canny, Prewitt, Sobel or Robert's edge detection. These edge detection techniques/algorithms help identify the location of certain facial features within the composition of pixels that correspond to the actual facial features of the user presented for image capture. For example, edge detection technology can first identify the user's face within the image, and also identify pixel locations within the image that correspond to specific facial features, such as each eye and its borders, the mouth and its corners, the left and right wings of the nose, and the bridge of the nose. points, suprasmental points, glabella points, and left and right nasolabial folds, etc. Processor 310 may then mark, annotate, or store the specific pixel location for each of these features. Alternatively, or if such detection by processor 310/server 210 is unsuccessful, it may be manually detected and marked, annotated, or Stores pre-assigned facial features.
一旦识别了这些面部特征的像素坐标，应用程序控制处理器310测量某些识别的特征之间的像素距离。例如，该距离通常可以由每个特征的像素的数量确定，并且可以包括缩放。例如，可以在左右鼻翼之间进行测量以确定鼻的像素宽度和/或在鼻梁点与颏上点之间进行测量以确定面部的像素高度。其他实例包括每只眼睛之间、嘴角之间以及左右鼻唇沟之间的像素距离，以获得像嘴一样的特定结构的附加测量数据。可以测量面部特征之间的进一步的距离。在该实例中，某些面部维度用于用户接口选择过程。Once the pixel coordinates of these facial features are identified, the application control processor 310 measures the pixel distances between certain identified features. For example, the distance may typically be determined by the number of pixels per feature, and may include scaling. For example, a measurement may be taken between the left and right nasal wings to determine the pixel width of the nose and/or a measurement may be taken between a bridge point and a supramaximal point to determine the pixel height of the face. Other examples include the pixel distance between each eye, between the corners of the mouth, and between the left and right nasolabial folds to obtain additional measurements of specific structures like the mouth. Further distances between facial features can be measured. In this example, certain facial dimensions are used in the user interface selection process.
一旦获得了预先指定的面部特征的像素测量，就可以将人体测量校正因子应用于这些测量。应当理解，可以在应用缩放因子之前或之后应用该校正因子，如下所述。人体测量校正因子可以校正自动过程中可能出现的误差，可以观察到这些误差在用户与用户之间一致地出现。换句话说，在没有校正因子的情况下，单独的自动过程可能导致从用户到用户的一致结果，但是这些结果可能引发一定量的尺寸制定不符的用户接口。可以根据经验从群体测试中提取的校正因子将结果移动得更接近真实测量，这有助于减少或消除尺寸制定不符。随着针对每个用户的测量和尺寸制定数据从相应的计算装置传送到服务器210(在该服务器210中可以进一步处理此类数据以改善该校正因子)，该校正因子的准确度可以随时间得到改进或改善。人体测量校正因子也可以在用户接口的形式之间变化。例如，寻找FFM的特定用户的校正因子可以不同于寻找鼻罩时的校正因子。这种校正因子可以从面罩购买的跟踪中导出，诸如通过监测面罩返回并确定替换面罩和返回的面罩之间的尺寸差异。Once pixel measurements of prespecified facial features are obtained, anthropometric correction factors can be applied to these measurements. It should be understood that the correction factor may be applied before or after the scaling factor is applied, as described below. Anthropometric correction factors correct for possible errors in the automated process, which can be observed to occur consistently from user to user. In other words, without correction factors, automated processes alone may lead to consistent results from user to user, but these results may induce a certain amount of sizing inconsistent user interfaces. Correction factors that can be empirically extracted from population testing move results closer to true measurements, which can help reduce or eliminate sizing discrepancies. The accuracy of the correction factor can be determined over time as measurement and sizing data for each user is transmitted from the respective computing device to the server 210 (where such data can be further processed to improve the correction factor). improve or ameliorate. Anthropometric correction factors can also vary between forms of user interface. For example, the correction factor for a specific user when looking for FFM may be different from the correction factor when looking for a nasal mask. Such correction factors may be derived from tracking of mask purchases, such as by monitoring mask returns and determining the size difference between replacement masks and returned masks.
为了将面部特征测量应用于用户接口尺寸制定，不管是由人体测量校正因子校正还是未校正，可以将这些测量从像素单位缩放为准确地反映如呈现用于图像捕捉的用户的面部特征之间的距离的其他值。参考特征可以用于获得一个或多个缩放值。因此，处理器310类似地确定参考特征的维度，这些参考特征的维度可以包括整个参考特征的像素宽度和/或像素高度(x和y)测量(例如，像素计数)。还可以确定包括QR码参考特征的许多正方形/点的像素维度，和/或由参考特征及其组成部分占据的像素面积的更详细的测量。因此，可以以像素为单位来测量QR码参考特征的每个正方形或点，以基于每个点的像素测量确定缩放因子，并且然后在测量的全部正方形或点之间进行平均，与QR码参考特征的完整尺寸的单个测量相比，这可以提高缩放因子的准确度。然而，应当理解，无论采取参考特征的何种测量，均可以利用这些测量将参考特征的像素测量缩放为参考特征的对应的已知维度。To apply facial feature measurements to user interface sizing, whether corrected or uncorrected by anthropometric correction factors, these measurements can be scaled from pixel units to accurately reflect the differences between the user's facial features as presented for image capture. Other values for distance. Reference features can be used to obtain one or more scaling values. Accordingly, processor 310 similarly determines dimensions of the reference features, which may include pixel width and/or pixel height (x and y) measurements (eg, pixel counts) of the entire reference feature. It is also possible to determine the pixel dimensions of the many squares/dots that comprise the QR code reference feature, and/or a more detailed measurement of the pixel area occupied by the reference feature and its components. Therefore, each square or point of the QR code reference feature can be measured in pixels to determine a scaling factor based on the pixel measurements of each point, and then averaged across all squares or points measured, with the QR code reference This can improve the accuracy of the scaling factor compared to a single measurement of the feature's full size. However, it should be understood that whatever measurements of the reference feature are taken, these measurements can be used to scale the pixel measurements of the reference feature to the corresponding known dimensions of the reference feature.
一旦由处理器310进行了参考特征的测量，就由如由应用程序控制的处理器310计算缩放因子。参考特征的像素测量与该参考特征(例如，如由用于图像捕捉的显示界面320显示的参考特征326)的已知对应的维度有关，以获得转换或缩放因子。这种缩放因子可以是长度/像素或面积/像素A2的形式。换句话说，已知维度可以除以对应的像素测量(例如，计数)。Once the measurement of the reference feature is made by the processor 310, the scaling factor is calculated by the processor 310, as controlled by an application program. Pixel measurements of a reference feature are related to known corresponding dimensions of the reference feature (eg, reference feature 326 as displayed by display interface 320 for image capture) to obtain a conversion or scaling factor. This scaling factor can be in the form of length/pixel or area/pixel A2. In other words, a known dimension can be divided by the corresponding pixel measurement (eg, count).
然后，处理器310将缩放因子应用于面部特征测量(像素计数)，以将测量从像素单位转换为其他单位，以反映适合于面罩尺寸制定的用户的实际面部特征之间的距离。这通常可以包括将缩放因子乘以与面罩尺寸制定相关的面部特征的距离的像素计数。The processor 310 then applies a scaling factor to the facial feature measurement (pixel count) to convert the measurement from pixel units to other units to reflect the distance between the actual facial features of the user appropriate to the mask sizing. This may typically involve multiplying a scaling factor by the pixel count of the distance to the facial feature relevant to mask sizing.
针对每个捕捉的图像重复面部特征以及参考特征的这些测量步骤和计算步骤，直到集合中的每个图像均具有经缩放和/或经校正的面部特征测量。These measurement steps and calculation steps of facial features as well as reference features are repeated for each captured image until every image in the collection has scaled and/or corrected facial feature measurements.
然后，处理器310可以可选地对该图像集合的经校正和经缩放的测量进行平均，以获得用户的面部解剖结构的最终测量。此类测量可以反映用户的面部特征之间的距离。Processor 310 may then optionally average the corrected and scaled measurements of the set of images to obtain a final measurement of the user's facial anatomy. Such measurements can reflect the distance between a user's facial features.
在比较和输出阶段，来自捕捉后图像处理阶段的结果可以直接输出(显示)给感兴趣的人，或与数据记录进行比较以获得用户接口尺寸的自动推荐。In the comparison and output stage, the results from the post-capture image processing stage can be output (displayed) directly to interested parties, or compared with data records to obtain automatic recommendations for user interface dimensions.
一旦确定了全部测量，处理器310就可以经由显示界面320向用户显示结果(例如，平均值)。在一个实施例中，这可以结束自动过程。用户/患者可以记录这些测量以供用户进一步使用。Once all measurements are determined, processor 310 may display the results (eg, averages) to the user via display interface 320 . In one embodiment, this may end the automated process. The user/patient can record these measurements for further use by the user.
或者，最终测量可以自动地或在用户的命令下经由通信网络220从计算装置230转发到服务器210。服务器210或服务器侧的个体可以进行进一步的处理和分析以确定合适的用户接口和用户接口尺寸。Alternatively, the final measurements may be forwarded from computing device 230 to server 210 via communication network 220 automatically or at the user's command. Server 210 or an individual on the server side may perform further processing and analysis to determine the appropriate user interface and user interface dimensions.
在另外的实施例中，由处理器310将反映用户的实际面部特征之间的距离的最终面部特征测量与诸如数据记录中的用户接口尺寸数据进行比较。数据记录可以是用于自动面部特征测量和用户接口尺寸制定的应用程序的一部分。该数据记录可以包括例如可以由处理器310访问的查找表，该查找表可以包括对应于面部特征距离/值的范围的用户接口尺寸。数据记录中可以包括多个表，多个表中的许多表可以对应于特定形式的用户接口和/或由制造商提供的特定型号的用户接口。In further embodiments, the final facial feature measurements, which reflect the distance between the user's actual facial features, are compared by processor 310 to user interface size data, such as in the data record. Data logging may be part of an application for automated facial feature measurement and user interface sizing. The data record may include, for example, a lookup table accessible by processor 310, which may include user interface dimensions corresponding to a range of facial feature distances/values. A plurality of tables may be included in the data record, and many of the plurality of tables may correspond to a particular form of user interface and/or a particular model of user interface provided by the manufacturer.
用于选择用户接口的示例过程从通过上述方法捕捉的面部图像中识别关键界标。在该实例中，与潜在接口的初始相关性涉及包括面部高度、鼻宽度和鼻深度的面部界标，如图3A至图3B中的线3010、3020和3030表示。这三个面部界标测量由应用程序收集，以帮助诸如通过上述的一个或多个查找表来选择兼容面罩的尺寸。或者，与面部3D形状相关的其他数据也可以用于将导出的形状数据与如上所述的可用面罩的表面进行匹配。例如，可以通过将3D形变模型(3DMM)适配到用户的3D面部扫描来获得界标和面部的任何区域(即嘴、鼻等)。这种适配过程也称为非刚性配准或(收缩)包装。一旦3DMM配准到3D扫描，则可以使用任何数量的方法来确定面罩尺寸，因为用户面部的点和表面都是已知的。An example process for selecting a user interface identifies key landmarks from facial images captured via the method described above. In this example, the initial correlation to the potential interface involves facial landmarks including facial height, nasal width, and nasal depth, represented by lines 3010, 3020, and 3030 in Figures 3A-3B. These three facial landmark measurements are collected by the application to aid in selecting compatible mask sizes, such as through one or more of the lookup tables described above. Alternatively, other data related to the 3D shape of the face can also be used to match the derived shape data to the surface of the available mask as described above. For example, landmarks and any region of the face (i.e. mouth, nose, etc.) can be obtained by fitting a 3D deformable model (3DMM) to a 3D face scan of the user. This fitting process is also called non-rigid registration or (shrink) wrapping. Once the 3DMM is registered to the 3D scan, any number of methods can be used to determine mask size since the points and surfaces of the user's face are known.
图8A是诸如由上述应用程序捕捉的面部图像800，该面部图像800可用于确定面部高度维度、鼻宽度维度和鼻深度维度。图像800包括一系列界标点810，这些界标点810可以经由任何标准已知的方法根据图像800确定。在该实例中，有100个Standard Cyborg界标点被识别并显示在面部图像800上。在该实例中，该方法需要面部图像上的七个界标来确定面部高度、鼻宽度和鼻深度，用于与用户相关的面罩尺寸制定。如将要解释的，可以使用两个现有的界标(例如基于Standard Cyborg界标)。三维位置需要经由处理方法在图像上识别五个附加界标。基于成像数据和/或现有界标，可以确定新的界标。将使用的两个现有界标包括鼻梁点(鼻梁)上的点和鼻尖上的点。需要的五个新界标包括颏上点(下巴的顶部)、左鼻翼点和右鼻翼点，以及左鼻翼-面部沟点和右鼻翼-面部沟点。Figure 8A is a facial image 800, such as captured by the application described above, which may be used to determine facial height dimensions, nose width dimensions, and nose depth dimensions. Image 800 includes a series of landmark points 810 that may be determined from image 800 via any standard known method. In this example, 100 Standard Cyborg landmark points are recognized and displayed on facial image 800. In this instance, the method requires seven landmarks on the facial image to determine facial height, nose width, and nose depth for user-related mask sizing. As will be explained, two existing landmarks can be used (eg based on the Standard Cyborg landmark). The three-dimensional location requires processing to identify five additional landmarks on the image. Based on imaging data and/or existing landmarks, new landmarks can be determined. Two existing landmarks that will be used include points on the bridge of the nose (bridge of the nose) and points on the tip of the nose. The five new landmarks required include the suprammental point (top of the chin), left and right alar points, and left alar-facial sulcus point and right alar-facial sulcus point.
图8B示出了面部图像800，在该面部图像800中面部高度维度(鼻梁点到颏上点)经由界标点812和界标814来定义。界标812是鼻梁点上的现有界标点。界标点814是颏上点。根据界标点812和界标点814之间的距离确定面部高度维度。FIG. 8B shows a facial image 800 in which the facial height dimension (bridge point to supramental point) is defined via landmark points 812 and 814 . Landmark 812 is an existing landmark point on the bridge of the nose point. Landmark point 814 is the suprasmental point. The facial height dimension is determined based on the distance between landmark point 812 and landmark point 814.
图8C示出了具有新的界标点820和822以定位鼻宽度维度的面部图像800。这需要两个新的界标，一个在鼻的每一侧。这些被称为右鼻翼点和左鼻翼点，并且可以对应于右鼻翼端和左鼻翼端。这些点之间的距离提供了鼻宽度维度。鼻翼点不同，但类似于鼻翼-面部沟点。Figure 8C shows facial image 800 with new landmark points 820 and 822 to locate the nose width dimension. This requires two new landmarks, one on each side of the nose. These are called right alar points and left alar points, and may correspond to right alar ends and left alar ends. The distance between these points provides the nasal width dimension. The alar points are different but similar to the alar-facial groove points.
图8D示出了具有界标点830、832和834以确定鼻深度维度的面部图像800。对于鼻尖处的界标点830可获得合适的界标。界标点832和834被确定在鼻的左侧和右侧。界标点832和834位于鼻的左侧和右侧上的鼻翼-面部沟处。这些类似于鼻翼点，但在鼻的后部。Figure 8D shows facial image 800 with landmark points 830, 832, and 834 to determine the nasal depth dimension. Suitable landmarks are obtained for the landmark point 830 at the tip of the nose. Landmark points 832 and 834 are identified on the left and right sides of the nose. Landmark points 832 and 834 are located at the alar-facial grooves on the left and right sides of the nose. These are similar to alar points, but at the back of the nose.
如上所解释，可以为大的用户群体收集每个RPT装置的操作数据。这可以包括基于每个用户何时操作RPT装置和操作的持续时间的使用数据。因此，可以根据收集的操作数据确定依从性数据，诸如用户在预定时间段内使用RPT装置多长时间和用户在预定时间段内多久使用一次RPT装置，使用的治疗压力和/或RPT装置的使用量和使用方式是否与用户的呼吸治疗处方一致。例如，一个依从性标准可以是用户在90天的时间段内可接受地使用RPT装置。泄漏数据可以根据诸如流速数据或压力数据的分析的操作数据确定。可以导出使用声学信号分析的面罩切换数据，以确定用户是否正在切换面罩。RPT装置可以正常操作以基于内部或外部音频传感器(诸如图4B中的音频传感器4278)使用如上文所解释的倒谱分析来确定面罩类型。或者，对于较老的面罩，可以使用操作数据通过将收集的声学数据与已知面罩的声学特征标记相关联来确定面罩的类型。As explained above, operational data for each RPT device can be collected for a large user population. This may include usage data based on when each user operates the RPT device and the duration of the operation. Accordingly, compliance data may be determined based on collected operational data, such as how long the user used the RPT device during a predetermined time period and how often the user used the RPT device during a predetermined time period, the treatment pressure used and/or the usage of the RPT device Dosage and usage are consistent with the user’s respiratory treatment prescription. For example, one compliance criterion could be the user's acceptable use of the RPT device over a 90-day period. Leakage data may be determined based on analysis of operating data such as flow rate data or pressure data. Mask switching data using acoustic signal analysis can be exported to determine whether the user is switching masks. The RPT device may operate normally to determine the mask type based on an internal or external audio sensor (such as audio sensor 4278 in Figure 4B) using cepstrum analysis as explained above. Alternatively, for older masks, operational data can be used to determine the type of mask by correlating the collected acoustic data with known acoustic signature signatures of the mask.
在该实例中，可以经由在计算装置230上执行的用户应用程序来收集其他数据的用户输入。用户应用程序可以是指导用户获得面部界标特征的用户应用程序360的一部分或单独的应用程序。这还可以包括经由带有问题的问卷获得的主观数据，以采集关于舒适度偏好的数据，用户是嘴还是鼻呼吸者(例如，诸如“你醒来嘴干吗？”的问题)，以及面罩材料偏好，诸如硅酮、泡沫、织物、凝胶。例如，用户输入可以通过经由用户应用程序响应于与用户接口的舒适度有关的主观问题的用户来采集。其他问题可能涉及相关的用户行为，诸如睡眠特性。例如，主观问题可以包括诸如你醒来嘴干吗？你是嘴呼吸者吗？或您的舒适度偏好是什么？的问题此类睡眠信息可以包括睡眠时长、用户如何睡眠，以及诸如温度、压力因素等的外部影响。主观数据可以简单到关于舒适度或更详细的响应的数字评级。此类主观数据也可以从图形用户界面(GUI)收集。例如，关于用户在治疗期间经历的来自用户接口的泄漏的输入数据可以通过用户选择在GUI上的用户接口的图形上显示的用户接口的部分来收集。收集的用户输入数据可以分配给图7中的用户数据库260。来自用户的主观输入数据可用作选择示例面罩类型和尺寸的输入。可以收集与用户的心理安全有关的其他主观数据。例如，可以询问诸如用户使用该特定面罩是否感觉到幽闭恐怖症或者用户在他们的床伴旁边佩戴面罩感觉心理舒适度如何的问题，并且可以收集输入。如果对这些问题的回答位于指示否定响应的下部端，则系统可以从接口数据库270中推荐不那么令人讨厌的接口，诸如比用户的现有面罩小的面罩，该面罩可以是鼻托面罩(在用户鼻的下周边处密封到用户面部并使用户的嘴和鼻梁不被覆盖的面罩)或围绕用户的嘴且也在用户鼻的下周边处密封但不接合鼻梁的鼻和嘴面罩(其可以被称为超紧凑型全面部面罩)。关于优选的睡眠位置的其他问题以及关于用户是否喜欢在晚上四处过多移动的问题也可以包括在内，并且用户将更喜欢可以允许更多移动的管向上面罩(例如，具有导管头戴设备的面罩)形式的‘自由’。或者，如果用户倾向于仍然仰卧或侧躺，则管下面罩(例如，具有从靠近用户的鼻或嘴的位置处的面罩向前和/或向下延伸的管的传统类型的面罩)将是可接受的。In this example, user input of other data may be collected via a user application executing on computing device 230 . The user application may be part of the user application 360 or a separate application that guides the user to obtain facial landmark features. This can also include subjective data via questionnaires with questions to collect data on comfort preferences, whether the user is a mouth or nasal breather (e.g., questions such as "Do you wake up with a dry mouth?"), and mask materials Preferences such as silicone, foam, fabric, gel. For example, user input may be collected by a user responding to subjective questions related to comfort of the user interface via the user application. Other questions may involve related user behavior, such as sleep characteristics. For example, subjective questions could include things like: Do you wake up with a dry mouth? Are you a mouth breather? Or what are your comfort preferences? Questions like this sleep information can include sleep duration, how the user sleeps, and external influences such as temperature, stress factors, etc. Subjective data can be as simple as a numerical rating on comfort or more detailed response. Such subjective data can also be collected from graphical user interfaces (GUIs). For example, input data regarding leakage from the user interface experienced by the user during treatment may be collected by the user selecting portions of the user interface displayed on a graphic of the user interface on the GUI. The collected user input data can be assigned to user database 260 in Figure 7. Subjective input data from users can be used as input for selecting example mask types and sizes. Other subjective data related to the user's psychological safety can be collected. For example, questions such as whether the user feels claustrophobic using that particular mask or how psychologically comfortable the user feels wearing the mask next to their bed partner can be asked and input can be collected. If the answers to these questions are at the lower end indicating a negative response, the system may recommend a less objectionable interface from the interface database 270, such as a smaller mask than the user's existing mask, which may be a nosepiece mask ( A mask that seals to the user's face at the lower perimeter of the user's nose and leaves the user's mouth and bridge of the nose uncovered) or a nose and mouth mask that surrounds the user's mouth and also seals at the lower perimeter of the user's nose but does not engage the bridge of the nose (which Can be called an ultra-compact full face mask). Additional questions about preferred sleeping position and questions about whether the user likes to move around too much at night may also be included, and the user will prefer a tube-up mask that allows for more movement (e.g., a headset with a tube mask) form of 'freedom'. Alternatively, if the user prefers to still lie on their back or side, an under-tube mask (e.g., a traditional type of mask with tubes extending forward and/or downward from the mask near the user's nose or mouth) would be acceptable.
其他数据源可以在RPT装置的使用之外收集可能与面罩选择相关的数据。这可以包括用户人口统计数据，诸如年龄、性别或位置；AHI严重度指示用户经历的睡眠呼吸暂停的水平。另一实例可以是基于面部的计算机断层摄影(CT)扫描来确定软组织厚度。其他数据可以是RPT装置的新用户的规定压力设置。如果用户被指定较低的压力，诸如10cm H2O，这可以使用户能够佩戴适合于较低压力的较轻面罩，从而与具有更适合于20cm H2O但是可以产生更小的舒适度的非常坚固的密封的全面部相比，在面部上产生更大的舒适度和/或较小的面罩。然而，如果用户具有高压力要求，例如20cm H2O，则可向用户推荐具有非常坚固的密封的全面部面罩。Other data sources can collect data outside of the use of the RPT device that may be relevant to mask selection. This can include user demographics such as age, gender, or location; AHI severity indicates the level of sleep apnea the user experiences. Another example may be based on computed tomography (CT) scans of the face to determine soft tissue thickness. Other data may be the prescribed pressure settings for new users of the RPT device. If the user is specified for a lower pressure, such as 10cm H2O, this may enable the user to wear a lighter mask suitable for the lower pressure, as opposed to having a very strong seal that is better suited for 20cm H2O but may produce less comfort Produces greater comfort and/or a smaller mask on the face compared to a full face mask. However, if the user has high pressure requirements, such as 20cm H2O, a full face mask with a very strong seal may be recommended to the user.
在选择面罩之后，该系统继续从RPT装置250收集操作数据。收集的数据添加到数据库260和数据库270。来自新用户和现有用户的反馈可用于改进推荐，用于为后续用户提供更好的面罩选项。例如，如果操作数据确定推荐的面罩具有高水平的泄漏，则可以向用户推荐另一面罩类型。通过反馈回路，可以改进选择算法以学习最适合于特定面罩的面部几何形状的特定方面。该相关性可用于使用该面部几何形状来改进对新用户的面罩推荐。收集的数据和相关的面罩类型数据因此可以提供对面罩的选择标准的附加更新。因此，该系统可以为用户提供用于改善面罩的选择的附加见解。After selecting the mask, the system continues to collect operational data from the RPT device 250. The collected data is added to database 260 and database 270. Feedback from new and existing users can be used to improve recommendations and provide better face mask options for subsequent users. For example, if operational data determines that a recommended mask has a high level of leakage, another mask type may be recommended to the user. Through feedback loops, the selection algorithm can be refined to learn specific aspects of facial geometry that are best suited for a specific mask. This correlation can be used to use this facial geometry to improve mask recommendations for new users. The data collected and associated mask type data can therefore provide an additional update on the selection criteria for masks. Therefore, the system can provide users with additional insights for improving mask selection.
除了面罩选择之外，该系统可以允许分析与呼吸治疗有效性和用户依从性有关的面罩选择。附加数据允许基于通过反馈回路的数据来优化呼吸治疗。In addition to mask selection, the system may allow analysis of mask selection in relation to respiratory therapy effectiveness and user compliance. Additional data allows optimization of respiratory therapy based on data passing through the feedback loop.
可以应用机器学习来优化面罩选择过程，并提供面罩类型和增加用户对呼吸治疗的依从性之间的相关性。这种机器学习可以由服务器210执行。基于有利的操作结果的输出和包括用户人口统计、面罩尺寸和类型以及从用户收集的主观数据的输入，可以用训练数据集合来训练面罩选择算法。机器学习可用于发现期望的面罩尺寸和诸如面部维度、用户人口统计、来自RPT装置的操作数据和环境条件的预测输入之间的相关性。机器学习可以采用诸如神经网络、聚类或传统回归技术的技术。测试数据可用于测试不同类型的机器学习算法，并确定哪一个具有与预测相关性有关的最佳准确度。Machine learning can be applied to optimize the mask selection process and provide correlations between mask type and increased user compliance with respiratory treatments. This machine learning can be performed by server 210. A training data set can be used to train a mask selection algorithm based on outputs of favorable operating results and inputs including user demographics, mask size and type, and subjective data collected from users. Machine learning can be used to discover correlations between desired mask sizes and predictive inputs such as facial dimensions, user demographics, operational data from the RPT device, and environmental conditions. Machine learning can employ techniques such as neural networks, clustering, or traditional regression techniques. Test data can be used to test different types of machine learning algorithms and determine which one has the best accuracy with respect to predictive relevance.
用于选择最佳接口的模型可以通过来自图7中的系统的新输入数据持续地更新。因此，随着分析平台的更多使用，该模型可以变得更准确。The model used to select the best interface can be continuously updated with new input data from the system in Figure 7. Therefore, with greater use of the analytics platform, the model can become more accurate.
如上所解释，图6中的系统的一部分涉及向使用RPT装置的用户推荐接口。该系统的第二功能是包括接口选择的优化的验证过程。一旦向用户提供了推荐的面罩并使用该推荐的面罩一段时间，诸如两天、两周或另一段时间，该系统就可以监视RPT装置使用并收集其他数据。基于该收集的数据，如果根据指示泄漏、不良或下降依从性或不令人满意的反馈的不利数据确定面罩没有达到高标准，则系统可以重新评估面罩选择，并使用结果为用户更新数据库260和机器学习算法。该系统然后可以推荐新的面罩以适合新的收集的数据。例如，如果根据基于声学特征标记或其他传感器的数据确定相对高的泄漏率，则用户可能在REM睡眠期间颚靠下，这可能表明需要不同类型的接口，诸如全面部面罩而不是最初选择的仅鼻或较小的全面部面罩。As explained above, part of the system in Figure 6 involves recommending interfaces to users using RPT devices. A secondary function of the system is an optimized verification process involving interface selection. Once a user is provided with a recommended mask and uses the recommended mask for a period of time, such as two days, two weeks, or another period of time, the system can monitor RPT device usage and collect other data. Based on this collected data, if it is determined that the mask is not of a high standard based on adverse data indicating leakage, poor or declining compliance, or unsatisfactory feedback, the system can re-evaluate the mask selection and use the results to update the database 260 for the user and Machine learning algorithms. The system can then recommend new masks to fit the new collected data. For example, if a relatively high leakage rate is determined based on data based on acoustic signatures or other sensors, the user may have lowered their jaw during REM sleep, which may indicate the need for a different type of interface, such as a full-face mask rather than the initially selected only Nasal or smaller full face mask.
该系统还可以响应于满意的跟进数据来调整推荐。例如，如果操作数据指示选择的全面部面罩没有泄漏，则该例程可以推荐尝试较小的面罩以获得更好的体验。可以使用风格、材料、变化、与用户偏好的相关性之间的权衡以最大化用户对治疗的依从性来提供后跟进推荐。个体用户的权衡可以通过由应用程序向用户显示的输入树来确定。例如，如果用户指示皮肤刺激是来自潜在问题的菜单的一个问题，则可以显示具有面部图像上的潜在刺激的位置的图形，以从用户收集诸如刺激的特定位置的数据。特定数据可以为特定用户提供与最佳面罩的更好相关性。The system can also adjust recommendations in response to satisfactory follow-up data. For example, if operational data indicates that a selected full-face mask does not leak, the routine could recommend trying a smaller mask for a better experience. Post-follow-up recommendations can be provided using trade-offs between styles, materials, variations, and relevance to user preferences to maximize user compliance with treatment. Individual user tradeoffs can be determined through the input tree displayed to the user by the application. For example, if the user indicates that skin irritation is a problem from a menu of potential problems, a graph with the location of the potential irritation on the facial image can be displayed to collect data from the user such as the specific location of the irritation. Specific data can provide a better correlation with the best mask for a specific user.
图9是可以由图7中的服务器210执行的接口选择引擎执行的用户接口选择的过程的流程图。该过程收集用户的面部的图像(面部图像)，然后可以将该图像存储在存储装置上。该系统200可以包括面部轮廓引擎，该面部轮廓引擎可操作以基于该面部图像确定患者的面部特征。在一些实例中，面部轮廓引擎可以执行涉及面部分析的任何步骤。在该实例中，经由诸如图7中的智能电话234或平板电脑236的移动装置上的深度相机来扫描用户的面部，以产生面部的3D图像(900)。或者，3D面部扫描数据可以从具有已经扫描的用户的2D或3D面部图像的存储装置获得。根据面部3D扫描在面部网格中确定界标点，并且根据图像测量与用户接口适配性有关的关键维度和点的收集，诸如面部高度、鼻深度和鼻宽度(902)。然后按照尺寸和类型将测量的关键维度与潜在接口关联(904)。例如，关联性可以包括与3DMM的适配性或非刚性配准。来自3D扫描的不规则三角形表面网格与3DMM表面适配，该3DMM表面含有关于面部的信息，包括关键面部分区的位置和区域。FIG. 9 is a flowchart of a process of user interface selection that may be performed by the interface selection engine executed by server 210 in FIG. 7 . This process collects an image of the user's face (facial image), which can then be stored on a storage device. The system 200 may include a facial profiling engine operable to determine facial features of a patient based on the facial image. In some instances, the facial contouring engine can perform any step involving facial analysis. In this example, the user's face is scanned via a depth camera on a mobile device, such as smartphone 234 or tablet 236 in Figure 7, to produce a 3D image of the face (900). Alternatively, the 3D facial scan data may be obtained from a storage device having 2D or 3D facial images of the user that have been scanned. Landmark points are determined in the facial mesh from the facial 3D scan, and a collection of key dimensions and points related to user interface suitability, such as facial height, nose depth, and nose width, are measured from the images (902). The measured key dimensions are then associated with potential interfaces by size and type (904). For example, associativity may include adaptability or non-rigid registration to the 3DMM. An irregular triangular surface mesh from the 3D scan is fit to a 3DMM surface that contains information about the face, including the locations and regions of key facial partitions.
从与呼吸装置和对应的用户接口有关的数据库收集操作数据(906)。分析与期望的效果有关的操作数据，该期望的效果是诸如泄漏的减少和对涉及呼吸治疗装置的使用的呼吸治疗的最佳依从性。然后将确定的面部维度和点的期望的效果的操作数据与可用接口的不同尺寸和类型关联(908)。基于操作数据与面部维度和点之间的关联性，采用模型来选择适当的接口，以获得说明使泄漏最小化、最佳适配性以及对使用呼吸治疗装置的最佳依从性的期望的结果(910)。也可以考虑其他因素，包括用户输入，诸如对选择的接口的满意度。然后存储该选择的接口并将该选择的接口发送给用户(912)。如上所解释，一旦用户使用具有该选择的接口的RPT装置，扫描面部维度数据以及从RPT装置收集的数据就被添加到数据库260和数据库270以进一步改进选择过程的分析。Operational data is collected from a database related to the breathing device and corresponding user interface (906). The operational data are analyzed in relation to desired effects such as reduction of leakage and optimal compliance with respiratory therapy involving use of the respiratory therapy device. Operational data for the determined facial dimensions and desired effects of the points are then associated with the different sizes and types of available interfaces (908). Based on the correlation between operational data and facial dimensions and points, a model is employed to select an appropriate interface to obtain desired results that illustrate the minimization of leakage, optimal fit, and optimal compliance with the use of the respiratory therapy device (910). Other factors may also be considered, including user input, such as satisfaction with the selected interface. The selected interface is then stored and sent to the user (912). As explained above, once the user uses the RPT device with the selected interface, scanned facial dimensional data and data collected from the RPT device are added to database 260 and database 270 to further improve the analysis of the selection process.
图10是可以在图9中详述的接口的初始选择之后可以运行特定时间段或多个时间段的跟进例程。例如，可以在RPT装置使用该选择的接口的前两天内运行该跟进例程。如下面将解释的，图10中的例程可以提供继续使用初始选择的接口或切换到另一类型的接口的推荐。附加客观和主观数据的收集记录在接口数据库270中。因此，图10中的例程在接口数据库270中记录正在进行的使用、切换和反馈数据，以及最初选择为“成功”或“失败”的面罩类型中的标记。该数据持续地更新由服务器210执行的示例机器学习驱动的推荐引擎。Figure 10 is a follow-up routine that can be run for a specific time period or multiple time periods after the initial selection of the interface detailed in Figure 9. For example, the follow-up routine can be run within the first two days of the RPT device using the selected interface. As will be explained below, the routine in Figure 10 can provide recommendations to continue using the initially selected interface or to switch to another type of interface. The collection of additional objective and subjective data is recorded in interface database 270. Accordingly, the routine in Figure 10 records ongoing usage, switching and feedback data in the interface database 270, as well as a flag in the mask type initially selected as "success" or "failure". This data continuously updates the example machine learning-driven recommendation engine executed by server 210.
该例程首先在诸如使用的两天的设定时段内收集操作数据(1010)。例如，图2中的系统可以从两天的使用中收集符合的客观数据，诸如使用时间或来自RPT装置250的泄漏数据。当然，大于或小于两天的其他适当的时段可以用作从RPT装置收集操作数据和其他相关数据的时间段。The routine first collects operational data over a set period of time, such as two days of use (1010). For example, the system in Figure 2 may collect consistent objective data from two days of use, such as usage time or leakage data from RPT device 250. Of course, other suitable periods greater than or less than two days may be used as the time period for collecting operational data and other relevant data from the RPT device.
此外，可以从由计算装置230执行的用户应用程序的界面收集诸如密封质量/性能、舒适度、一般喜好/厌恶等的主观反馈数据(1012)。该主观数据可以通过经由双向通信装置或在计算装置230上执行的客户端应用程序询问的主观问题来收集。因此，该主观数据可以包括与不舒适或泄漏以及心理安全问题(诸如用户对面罩是否心理上舒适)有关的回答。该主观数据还可以包括由患者提供的关于清醒时间期间经历的疲劳的信息。Additionally, subjective feedback data such as seal quality/performance, comfort, general likes/dislikes, etc. may be collected from the interface of the user application executed by computing device 230 (1012). This subjective data may be collected through subjective questions asked via a two-way communication device or a client application executing on computing device 230. Therefore, this subjective data may include responses related to discomfort or leakage, as well as psychological safety questions, such as whether the user is psychologically comfortable with the mask. The subjective data may also include information provided by the patient regarding fatigue experienced during waking hours.
然后，该例程将客观数据和主观数据与选择的面罩尺寸/类型和用户的面部扫描数据关联(1014)。在良好结果的情况下，该例程将确定操作数据显示高依从性、低泄漏、和来自用户的良好主观结果数据(1016)。然后，该例程更新数据库和学习算法，作为与相关数据的成功匹配(1018)。该例程还分析相关数据并确定结果是否可以通过更期望的面罩来改善(1020)。然后该例程建议按照图9中的例程尝试更适当的面罩。The routine then associates the objective and subjective data with the selected mask size/type and the user's facial scan data (1014). In the case of good results, the routine will determine operational data showing high compliance, low leakage, and good subjective results data from the user (1016). The routine then updates the database and learning algorithm as a successful match to the relevant data (1018). The routine also analyzes relevant data and determines whether results could be improved with a more desirable mask (1020). The routine then recommends trying a more appropriate mask following the routine in Figure 9.
在来自关联性的不期望的结果的情况下(1014)，该例程确定不期望的结果是来自低依从性、高泄漏或不令人满意的主观结果数据中的至少一者(1022)。然后，该例程更新数据库270和学习算法，作为用户数据和选择的面罩之间的不成功匹配(1024)。然后该例程建议按照图9中的例程尝试更适当的面罩(1026)。In the case of undesirable results from correlation (1014), the routine determines that the undesirable results are from at least one of low compliance, high leakage, or unsatisfactory subjective outcome data (1022). The routine then updates the database 270 and learning algorithm as unsuccessful matches between the user data and the selected mask (1024). The routine then recommends trying a more appropriate mask (1026) following the routine in Figure 9.
如果用户按规定使用用户接口并且基于可以被同等地或不同地加权的多个因素，则可以将用户对治疗的依从性确定为高。用户接口的使用与规定用户使用该用户接口一样经常，可以计入对治疗的高依从性。在足够长的时段内使用该用户接口，诸如整个夜晚，而不是在夜晚期间中止治疗，也可以计入良好依从性。对其处方的一致坚持(例如，极少遗漏的夜晚)也计入良好依从性。此外，如果用户正在使用规定的治疗压力而不是较低的压力，则这可以促成良好依从性的评定。A user's compliance with treatment may be determined to be high if the user uses the user interface as prescribed and based on multiple factors that may be weighted equally or differently. Use of a user interface as often as the user is prescribed to use the user interface can count toward high compliance with treatment. Use of the user interface over a sufficiently long period of time, such as throughout the night, rather than discontinuing treatment during the night, may also count toward good compliance. Consistent adherence to their prescription (e.g., few missed nights) also counts as good compliance. Additionally, if the user is using the prescribed treatment pressure rather than a lower pressure, this may contribute to an assessment of good compliance.
在一些实例中，可以要求用户根据预定的替换时间表来替换他们的用户接口或其部件。例如，可能要求用户根据预定间隔基于规定的压力和使用强度替换他们的用户接口的衬垫模块，因为由于使用和清洁密封和通气口上的磨损可能不利地影响治疗的性能并因此影响治疗的有效性。在本技术的一些实例中，部件的及时替换可以计入对治疗的良好依从性的评定。如果处方数据不可用，则可以基于每周至少预定的夜晚数量(例如，至少4、5、6或7个夜晚)，持续至少预定的小时数量(例如，4、5、6或7个小时)，使用恒定的高治疗压力(例如，至少4、6、8或10cm H2O)来使用用户接口和对应的呼吸治疗装置和/或及时替换用户接口或其部件来确定用户依从性。In some instances, users may be required to replace their user interface or components thereof according to a predetermined replacement schedule. For example, users may be required to replace the pad modules of their user interfaces at predetermined intervals based on prescribed pressures and intensity of use, as wear on seals and vents due to use and cleaning may adversely affect the performance of the treatment and therefore the effectiveness of the treatment. . In some examples of the present technology, timely replacement of components may count toward an assessment of good compliance with treatment. If prescription data is not available, it may be based on at least a predetermined number of nights per week (e.g., at least 4, 5, 6, or 7 nights) for at least a predetermined number of hours (e.g., 4, 5, 6, or 7 hours) , use a constant high therapeutic pressure (eg, at least 4, 6, 8 or 10 cm H2O) with the user interface and corresponding respiratory therapy device and/or promptly replace the user interface or its components to determine user compliance.
如上所述，存在用户可以依从治疗的多种方式。在本技术的一些实例中，基于是否满足一个或多个标准来确定依从性程度是“不依从”还是“依从”。在一些实例中，依从性可以是“低”、“中”或“高”中的一者。在另外的实例中，依从性可以表示为出自100％的得分。良好的依从性水平不一定是100％，并且在一些实例中可以替代地是至少75％或80％。As mentioned above, there are various ways in which a user can comply with treatment. In some examples of the present technology, the degree of compliance is determined as "non-adherent" or "compliant" based on whether one or more criteria are met. In some examples, compliance may be one of "low," "medium," or "high." In other examples, compliance may be expressed as a score out of 100%. A good compliance level is not necessarily 100%, and in some instances may instead be at least 75% or 80%.
上述系统和移动装置还可以用于一旦使诸如面罩的物理用户接口对用户可用就确定适当的适配性。The systems and mobile devices described above may also be used to determine appropriate fit once a physical user interface, such as a mask, is made available to the user.
图11是根据本公开的一些实施方式的诸如用户10的用户的透视图，该用户控制诸如图7中的智能电话234的用户装置以收集与诸如面罩100的用户接口的当前适配性相关联的传感器数据。例如，用户10可以是诸如图1中的呼吸治疗系统的新用户。用户10可以刚刚戴上用户接口100，并且现在将用户装置234的一个或多个传感器朝向用户面部定向。面罩100可以是基于上述操作数据和面部数据而选择的面罩。尽管在图11中描绘为智能电话234，但可使用任何合适的用户装置。FIG. 11 is a perspective view of a user, such as user 10 , controlling a user device, such as smartphone 234 in FIG. 7 , to collect current fitness associated with a user interface, such as mask 100 , in accordance with some embodiments of the present disclosure. sensor data. For example, user 10 may be a new user of a respiratory therapy system such as in FIG. 1 . User 10 may have just put on user interface 100 and now orient one or more sensors of user device 234 toward the user's face. Mask 100 may be a mask selected based on the above operational data and facial data. Although depicted as a smartphone 234 in Figure 11, any suitable user device may be used.
为了获取测量，用户10可以按下适当的按钮或以其他方式与智能电话234交互以开始测量过程。一旦启动，智能电话234可以可选地向用户10提供指示用户10应当采取或停止的不同动作的刺激(例如，提示和/或指令)，以便实现期望的测量。例如，提示和/或指令可以包括文本指令，诸如“将电话保持在面部高度并以8字形缓慢移动”；听觉提示382，诸如当测量过程完成时的特定钟声播放；和/或触觉反馈380，诸如发信号通知用户10减慢智能电话234的移动的增加的振动模式。当智能电话234必须保持在禁止用户10观看智能电话234的显示器的取向时，使用非视觉提示(例如，听觉提示、触觉反馈等)可能特别有用。在一些情况下，提示和/或指令可呈现为用户10的图像上的叠加，诸如以增强现实叠加的形式。例如，图标、高亮显示、文本和其他标记可以叠加在用户10的图像(例如，实况或非实况)上以提供如何执行测量过程的指令。To obtain a measurement, user 10 may press the appropriate button or otherwise interact with smartphone 234 to begin the measurement process. Once activated, the smartphone 234 may optionally provide the user 10 with stimuli (eg, prompts and/or instructions) indicating different actions that the user 10 should take or stop in order to achieve the desired measurement. For example, prompts and/or instructions may include text instructions, such as "hold phone at face height and move slowly in a figure 8"; auditory prompts 382 , such as a specific chime that plays when the measurement process is complete; and/or tactile feedback 380 , such as an increased vibration pattern that signals the user 10 to slow down the movement of the smartphone 234 . The use of non-visual cues (eg, auditory cues, tactile feedback, etc.) may be particularly useful when the smartphone 234 must be maintained in an orientation that prohibits the user 10 from viewing the display of the smartphone 234 . In some cases, the prompts and/or instructions may be presented as an overlay on the image of user 10, such as in the form of an augmented reality overlay. For example, icons, highlights, text, and other indicia may be overlaid on the user's 10 image (eg, live or non-live) to provide instructions on how to perform the measurement process.
智能电话234可以包括一个或多个传感器。在一些情况下，可以指导用户10将智能电话234保持在特定取向，以确保期望的一个或多个传感器正在获取期望的数据。例如，当正在使用智能电话前面的红外传感器(例如，用于解锁电话的红外传感器)时，可以指导用户10握住电话使其面部面向智能电话234，使得红外传感器面向用户面部并获取用户面部的数据。在另一实例中，智能电话234可以在其后侧包括LiDAR传感器，在这种情况下，可以指导用户10握住电话使其面部背向用户10，使得LiDAR传感器面向用户面部并获取用户面部的数据。在一些情况下，可以指导用户10在智能电话234定位处于不同取向的情况下进行多次测量。Smartphone 234 may include one or more sensors. In some cases, the user 10 may be instructed to hold the smartphone 234 in a specific orientation to ensure that the desired sensor or sensors are acquiring the desired data. For example, when an infrared sensor on the front of a smartphone is being used (e.g., an infrared sensor used to unlock the phone), the user 10 may be instructed to hold the phone with his or her face facing the smartphone 234 so that the infrared sensor faces the user's face and obtains an image of the user's face. data. In another example, smartphone 234 may include a LiDAR sensor on its rear side, in which case user 10 may be instructed to hold the phone with his or her face facing away from user 10 so that the LiDAR sensor faces the user's face and acquires an image of the user's face. data. In some cases, the user 10 may be instructed to take multiple measurements with the smartphone 234 positioned in different orientations.
智能电话234可以提供关于用户接口100的当前适配性的反馈，无论是在测量过程期间(例如，实时反馈)和/或在测量过程结束之后(例如，非实时反馈)。在一个实例中，当用户10握住智能电话234以获取测量时，智能电话234可以提供指示用户10应当进行调整以改善用户接口100的当前适配性的反馈，诸如收紧特定的条带。在这种实例中，用户10可以在继续握住智能电话234的同时进行调整，使得其可以继续获取用户面部和/或用户接口100的测量。在此类情况下，智能电话234可以提供动态反馈，该动态反馈显示当前适配性是如何改善或以其他方式变化的。Smartphone 234 may provide feedback regarding the current suitability of user interface 100, either during the measurement process (eg, real-time feedback) and/or after the measurement process ends (eg, non-real-time feedback). In one example, when user 10 holds smartphone 234 to obtain measurements, smartphone 234 may provide feedback indicating that user 10 should make adjustments to improve the current fit of user interface 100, such as tightening certain straps. In such an instance, user 10 may make adjustments while continuing to hold smartphone 234 so that it may continue to obtain measurements of the user's face and/or user interface 100 . In such cases, smartphone 234 may provide dynamic feedback showing how current fit has improved or otherwise changed.
图12是根据本公开的一些实施方式的用于识别与用户接口100的当前适配性相关联的热特性的智能电话234的用户视图。智能电话234和用户接口100可以是任何合适的用户装置和用户接口。图12中描绘的视图可以在测量过程期间制成(例如，实况查看，诸如实时查看)或者可以在进行测量之后制成(例如，在测量过程完成之后查看)。Figure 12 is a user view of smartphone 234 for identifying thermal characteristics associated with current fit of user interface 100, in accordance with some embodiments of the present disclosure. Smartphone 234 and user interface 100 may be any suitable user device and user interface. The view depicted in Figure 12 may be made during the measurement process (eg, a live view, such as a real-time view) or may be made after the measurement is made (eg, viewed after the measurement process is completed).
用户10可以握住用户装置(例如，智能电话234)，使得他们能够看到智能电话234的显示装置472(例如，显示屏幕)。显示装置472可以描绘可以提供与用户接口100的当前适配性相关联的反馈的图形用户界面(GUI)。GUI可以包括佩戴用户接口100的用户10的图像。该图像可以由红外传感器获取，并且可以是佩戴用户接口100的用户10的热图。该热图可以描绘用户面部和用户接口100上的不同点处的局部温度。User 10 may hold the user device (eg, smartphone 234 ) such that they can see display device 472 (eg, display screen) of smartphone 234 . Display device 472 may depict a graphical user interface (GUI) that may provide feedback associated with the current suitability of user interface 100 . The GUI may include an image of user 10 wearing user interface 100. The image may be acquired by an infrared sensor and may be a heat map of the user 10 wearing the user interface 100 . The heat map may depict local temperatures at different points on the user's face and user interface 100 .
如放大视图所示，用户接口100和用户面部之间的密封附近的用户面部的分区482被示出为实质上比用户面部的周围分区冷。该较冷分区482可指示无意空气泄漏，因为从用户接口100的密封泄漏的空气可将用户的皮肤冷却IR传感器可察觉的量。As shown in the enlarged view, zones 482 of the user's face near the seal between the user interface 100 and the user's face are shown to be substantially cooler than surrounding zones of the user's face. This cooler zone 482 may indicate an unintentional air leak, as air leaking from the seal of the user interface 100 may cool the user's skin by an amount detectable by the IR sensor.
在一些情况下，GUI可以以与用户接口100的当前适配性相关联的得分484的形式提供反馈。例如，得分484可被描绘为可填充0％至100％之间的填充条。如图12中描绘的，用户接口100的当前适配性的得分484当前为大约65％。In some cases, the GUI may provide feedback in the form of a score 484 associated with the current suitability of the user interface 100 . For example, a score of 484 may be depicted as a fill bar that may fill between 0% and 100%. As depicted in Figure 12, the current suitability score 484 for the user interface 100 is currently approximately 65%.
在一些情况下，GUI可以以文本指令486的形式提供反馈，以改善当前适配性。文本指令486可以为用户10提供采取动作以改善当前适配性的指令，诸如收紧如图12中描绘的左上条带。选择了收紧左上条带的指令，因为这样做应该减少或消除由分区482处的热差异检测到的空气泄漏。In some cases, the GUI may provide feedback in the form of text instructions 486 to improve current fitness. Text instructions 486 may provide the user 10 with instructions to take action to improve the current fit, such as tightening the upper left band as depicted in FIG. 12 . The instruction to tighten the upper left strip was chosen because doing so should reduce or eliminate air leakage detected by the thermal differential at zone 482.
图13是根据本公开的一些实施方式的用于识别与用户接口的当前适配性相关联的基于轮廓的特性的用户装置(诸如智能电话234)的用户视图。该用户装置可以是任何合适的用户装置，诸如图7中示出的那些。Figure 13 is a user view of a user device, such as smartphone 234, for identifying contour-based characteristics associated with current suitability of a user interface, in accordance with some embodiments of the present disclosure. The user device may be any suitable user device, such as those shown in Figure 7.
智能电话234的显示装置572(例如，显示屏幕)可以显示包括用户10的实况图像的GUI。为了创建用户10的实况图像，智能电话234的相机550可以指向用户10。The display device 572 (eg, display screen) of the smartphone 234 may display a GUI including a live image of the user 10 . To create a live image of user 10 , camera 550 of smartphone 234 may be pointed at user 10 .
在图13中描绘的视图中，用户10刚刚移除了用户接口，留下围绕用户面部部分的压痕590。该压痕590可以通过视觉感测(例如，感测压痕590的颜色或压痕590与用户面部的邻近表面之间的颜色差异)、测距感测(例如，发送压痕590与用户面部的邻近表面之间的局部深度差异)等来检测。如所描绘的，压痕590的分区592不如其他分区明显。该分区592可被识别为用户接口未被充分压靠面部皮肤从而未建立有效密封的分区。In the view depicted in Figure 13, user 10 has just removed the user interface, leaving an indentation 590 surrounding portions of the user's face. The indentation 590 can be detected by visual sensing (e.g., sensing the color of the indentation 590 or a color difference between the indentation 590 and adjacent surfaces of the user's face), ranging sensing (e.g., transmitting the indentation 590 to the user's face). to detect local depth differences between adjacent surfaces), etc. As depicted, the zones 592 of the indentation 590 are less distinct than the other zones. This zone 592 may be identified as a zone where the user interface is not pressed sufficiently against the facial skin to establish an effective seal.
在一些情况下，GUI可以以与用户接口的当前适配性相关联的得分584的形式提供反馈。例如，分区592的范围可以指示用户接口的当前适配性(例如，在收集引发分区592的识别的传感器数据之前移除的用户接口的适配性)不是最佳的。可以生成并描绘得分584，诸如经由数值得分“65％”。在一些情况下，可另外提供警报，诸如指示检测到不良适配性的警报585。在一些情况下，GUI可以以文本指令586的形式提供反馈，以改善当前适配性。文本指令586可以为用户10提供采取动作以改善当前适配性的指令，诸如通过使用不同类型的用户接口(例如，鼻枕罩而不是全面部用户接口)。因为检测到的不良适配性和/或改善当前用户接口的适配性的一个或多个先前试图的本质，使用鼻枕罩而不是全面部用户接口的指令可能已经被选择。例如，如果用户试图改善当前用户接口的适配性超过阈值次数，则系统可确定尝试使用不同类型的用户接口来建立良好适配性可能是谨慎的。可用的用户接口可以使用结合了来自上述RPT装置的面部数据和操作数据的例程来选择。In some cases, the GUI may provide feedback in the form of a score 584 associated with the current suitability of the user interface. For example, the extent of partition 592 may indicate that the current suitability of the user interface (eg, the suitability of the user interface that was removed prior to collection of sensor data that led to the identification of partition 592) is not optimal. A score 584 may be generated and depicted, such as via a numerical score of "65%." In some cases, an alert may additionally be provided, such as alert 585 indicating that poor fit has been detected. In some cases, the GUI may provide feedback in the form of text instructions 586 to improve current fitness. Text instructions 586 may provide instructions for user 10 to take action to improve the current fit, such as by using a different type of user interface (eg, a nasal pillow mask rather than a full face user interface). Instructions to use a nasal pillow mask rather than a full face user interface may have been selected because of the nature of the detected poor fit and/or one or more previous attempts to improve the fit of the current user interface. For example, if a user attempts to improve the fit of the current user interface more than a threshold number of times, the system may determine that it may be prudent to try to establish good fit using a different type of user interface. The available user interfaces can be selected using routines that combine facial data and operational data from the RPT device described above.
当在图13中将压痕590检测为用户面部上的检测的轮廓时，在一些情况下，可以检测用户面部中的颜色变化(例如，热烫，或当一些血液被推动离开皮肤表面附近的组织时的颜色变化，其中用户接口的密封搁置在皮肤表面上)以识别用户接口的密封接合用户面部的位置和方式。While indentations 590 are detected as detected contours on the user's face in Figure 13, in some cases, color changes in the user's face may be detected (e.g., heat blanching, or when some blood is pushed away from near the skin surface Color change when organized (where the seal of the user interface rests on the surface of the skin) to identify where and how the seal of the user interface engages the user's face.
图14是描绘根据本公开的一些实施方式的用于评估用户接口跨用户接口转换事件的适配性的过程1400的流程图。该用户接口可以是任何合适的用户接口，诸如图1的用户接口100。该过程1400可以使用诸如智能电话234的处理器或诸如图7中的服务器210的服务器的处理器的控制系统来执行。在过程1400期间收集的传感器数据可以从一个或多个传感器(例如，图4A至图4C中的RPT装置40的一个或多个传感器)收集，该一个或多个传感器中的一个、多于一个或全部可以结合到用户装置中和/或联接到用户装置(例如，图7的智能电话234)。用户接口转换事件的实例包括戴上用户接口、移除用户接口、调整用户接口(例如，对用户接口的可调整部分进行调整，诸如可调整的条带；将用户接口移动到用户面部上的不同位置或取向；等等)，以及调整呼吸治疗系统，诸如联接到用户接口的RPT装置40(例如，打开或转动呼吸治疗系统；调整呼吸治疗系统的参数，诸如湿度或加热；等等)。Figure 14 is a flowchart depicting a process 1400 for evaluating the suitability of a user interface across user interface transition events in accordance with some embodiments of the present disclosure. The user interface may be any suitable user interface, such as user interface 100 of FIG. 1 . The process 1400 may be performed using a control system such as a processor of a smartphone 234 or a processor of a server such as server 210 in FIG. 7 . Sensor data collected during process 1400 may be collected from one or more sensors (eg, one or more sensors of RPT device 40 in FIGS. 4A-4C ), one or more of the sensors Or all may be incorporated into and/or coupled to a user device (eg, smartphone 234 of Figure 7). Examples of user interface transition events include putting on the user interface, removing the user interface, adjusting the user interface (e.g., making adjustments to an adjustable portion of the user interface, such as an adjustable strip; moving the user interface to a different position on the user's face). position or orientation; etc.), and adjust the respiratory therapy system, such as the RPT device 40 coupled to the user interface (e.g., turn on or rotate the respiratory therapy system; adjust parameters of the respiratory therapy system, such as humidity or heating; etc.).
在框1402处，可在戴上用户接口之前收集第一传感器数据。可以收集用户面部的第一传感器数据，并且可选地收集用户接口(在由用户戴上之前)的第一传感器数据。At block 1402, first sensor data may be collected prior to donning the user interface. First sensor data may be collected for the user's face, and optionally for the user interface (before being worn by the user).
在一些情况下，可以在框1412处使用第一传感器数据以识别与用户接口的潜在适配性相关联的一个或多个特性。例如，基于仅根据第一传感器数据识别的特性，系统可以确定用户将最适合于使用鼻枕罩而不是全面部用户接口(例如，如果在全面部用户接口密封通常处于的位置周围检测到特别大的轮廓，或者如果在全面部用户接口密封通常处于的位置周围检测到特别厚的胡须)。In some cases, the first sensor data may be used at block 1412 to identify one or more characteristics associated with potential suitability of the user interface. For example, based on characteristics identified based solely on the first sensor data, the system may determine that the user would be best suited to use a nasal pillow mask rather than a full-face user interface (e.g., if particularly large user interface seals are detected around the location where the full-face user interface seal would normally be located). outline, or if a particularly thick beard is detected around where the full-face UI seal would normally be).
然而，在一些情况下，在框1412处使用第一传感器数据与其他传感器数据进行比较。例如，在一些情况下，第一传感器数据可以建立用于将来比较的基线，诸如面部的基线轮廓图、面部的基线热图、面部的一个或多个特征的基线检测(例如，眼睛、嘴、鼻、耳朵等的检测)等。第一传感器数据可以被认为是与用户接口的当前适配性相关联的传感器数据，诸如如果在出于建立基线的目的而戴上用户接口之前收集到第一传感器数据，则将进一步的传感器数据与该基线进行比较以评估该用户接口在被佩戴时的适配性。例如，此类数据可以从如上参考图8A至图8D解释的执行的面部扫描存储。However, in some cases, the first sensor data is used for comparison with other sensor data at block 1412 . For example, in some cases, the first sensor data may establish a baseline for future comparisons, such as a baseline contour map of the face, a baseline heat map of the face, baseline detection of one or more features of the face (e.g., eyes, mouth, Nose, ears, etc.) etc. The first sensor data may be considered to be sensor data associated with the current fit of the user interface, such as if the first sensor data was collected before the user interface was donned for the purpose of establishing a baseline, then further sensor data A comparison is made to the baseline to evaluate the fit of the user interface when worn. For example, such data may be stored from a facial scan performed as explained above with reference to Figures 8A to 8D.
在框1404处，可戴上用户接口。戴上用户接口可以涉及用户将用户接口放置在用户面部上，就好像他们正在使用该用户接口一样(例如，用于呼吸治疗)。在一些情况下，在框1404处戴上用户接口可以包括在戴上用户接口之前对用户接口进行调整，尽管不必总是这种情况。在戴上用户接口之前对用户接口进行调整的情况下，可以将传感器数据的进一步分析与历史传感器数据、历史特性数据、历史适配性得分等进行比较。例如，在框1404处戴上用户接口可以紧跟在识别待采取以改善适配性的动作的用户接口适配性的先前评估之后发生。在这种实例中，用户可以将该动作作为框1404的一部分，然后将用户接口的得到的适配性与用户接口的先前适配性进行比较，以确定适配性是否已经改善。At block 1404, the user interface may be donned. Putting on the user interface may involve the user placing the user interface on the user's face as if they were using the user interface (eg, for respiratory therapy). In some cases, donning the user interface at block 1404 may include making adjustments to the user interface prior to donning the user interface, although this need not always be the case. Further analysis of the sensor data can be compared to historical sensor data, historical property data, historical fit scores, etc., in the event that the user interface is adjusted before being put on. For example, donning the user interface at block 1404 may occur immediately following a previous evaluation of user interface fit that identified actions to be taken to improve fit. In such an instance, the user may take this action as part of block 1404 and then compare the resulting fit of the user interface to the previous fit of the user interface to determine whether the fit has improved.
在一些情况下，在框1404处戴上用户接口可以包括佩戴用户接口达阈值持续时间。例如，如果通过比较佩戴用户接口之前和之后的传感器数据来进行用户接口适配性的评估，则过程1400可以从框1404前进到框1408。在此类情况下，为了确保佩戴用户接口达足够的持续时间以影响用户面部(例如，足够的持续时间以在用户面部中建立压痕或颜色变化)，在框1404处戴上用户接口可以包括佩戴用户接口达阈值时间量(例如，至少10秒、20秒、30秒、40秒、50秒、1分钟、1.5分钟、2分钟、5分钟、10分钟或15分钟)。In some cases, donning the user interface at block 1404 may include wearing the user interface for a threshold duration. For example, if the evaluation of user interface fit is performed by comparing sensor data before and after wearing the user interface, process 1400 may proceed from block 1404 to block 1408 . In such cases, to ensure that the user interface is worn for a sufficient duration to affect the user's face (e.g., for a sufficient duration to create an indentation or color change in the user's face), donning the user interface at block 1404 may include The user interface is worn for a threshold amount of time (eg, at least 10 seconds, 20 seconds, 30 seconds, 40 seconds, 50 seconds, 1 minute, 1.5 minutes, 2 minutes, 5 minutes, 10 minutes, or 15 minutes).
在框1406处，可以在佩戴用户接口(例如，佩戴在用户面部上)的同时收集第二传感器数据。可以收集用户面部和用户佩戴的用户接口的第二传感器数据。在一些情况下，可以在对用户接口和/或联接到用户接口的呼吸治疗系统进行一个或多个调整的同时收集第二传感器数据。在此类情况下，在框1412处，随时间取得的第二传感器数据可用于检测识别的特性的变化，该识别的特性的变化可用于评估用户接口的当前适配性。在一个实例中，当图1中的呼吸治疗系统的加热器被接合时，在框1406处收集的热数据可以识别用户面部的在用户接口之外并且与用户接口邻近的分区的温度的变化，指示在用户面部的该分区附近的用户接口的密封处可能存在无意空气泄漏。在这种实例中，诸如由图4C中的音频传感器4278收集的音频数据的附加传感器数据可用于确认泄漏的存在(例如，经由检测与无意泄漏相关联的特性声学信号，诸如听得见或听不到的信号)。At block 1406, second sensor data may be collected while the user interface is worn (eg, worn on the user's face). Second sensor data may be collected on the user's face and the user interface worn by the user. In some cases, the second sensor data may be collected while one or more adjustments are being made to the user interface and/or the respiratory therapy system coupled to the user interface. In such cases, at block 1412, the second sensor data taken over time may be used to detect changes in the identified characteristics, which may be used to evaluate the current suitability of the user interface. In one example, when a heater of the respiratory therapy system of Figure 1 is engaged, thermal data collected at block 1406 may identify changes in temperature of a zone of the user's face that is outside of and adjacent to the user interface, Indicates that there may be an inadvertent air leak from the seal of the user interface near this area of the user's face. In such instances, additional sensor data, such as the audio data collected by audio sensor 4278 in Figure 4C, may be used to confirm the presence of a leak (e.g., via detection of characteristic acoustic signals associated with inadvertent leaks, such as audible or auditory no signal).
在框1408处，可移除用户接口。可以在一个或多个传感器仍在收集传感器数据的同时执行用户接口的移除，尽管不必总是这种情况。At block 1408, the user interface may be removed. Removal of the user interface can be performed while one or more sensors are still collecting sensor data, although this need not always be the case.
在框1410处，可在用户已移除用户接口之后收集第三传感器数据。除了传感器数据受到由于已经佩戴用户接口而引起的用户面部变化的影响，第三传感器数据可以类似于来自框1402的第一传感器数据。At block 1410, third sensor data may be collected after the user has removed the user interface. The third sensor data may be similar to the first sensor data from block 1402, except that the sensor data is affected by changes in the user's face due to having worn the user interface.
在框1402、框1406和框1410处收集传感器数据可包括收集相同类型的传感器数据(包括来自相同或不同传感器的传感器数据)和/或不同类型的传感器数据。例如，分别在框1402和框1410处收集的第一传感器数据和第二传感器数据可以各自包括视觉和IR光谱中的测距传感器数据和图像数据，而在框1406处收集的第二传感器数据可以包括视觉和IR光谱中的音频数据和图像数据。Collecting sensor data at blocks 1402, 1406, and 1410 may include collecting the same type of sensor data (including sensor data from the same or different sensors) and/or different types of sensor data. For example, the first and second sensor data collected at blocks 1402 and 1410, respectively, may each include ranging sensor data and image data in the visual and IR spectra, while the second sensor data collected at block 1406 may Includes audio data and image data in the visual and IR spectrum.
在框1412处，根据传感器数据(例如，第一、第二和/或第三传感器数据)识别一个或多个特性。在框1412处识别特性可以包括分析给定的传感器数据集合(例如，单独分析的第二传感器数据)和/或比较传感器数据集合(例如，第一传感器数据与第三传感器数据进行比较)。在框1412处识别特性可以包括识别指示用户接口的适配性的质量的特性。例如，一些特性可以指示用户接口的不良适配性，而其他特性可以指示用户接口的良好适配性。在一个实例中，作为指示无意空气泄漏的声音的特性可以指示不良适配性，而作为佩戴用户接口的用户面部的热图的特性可以指示良好适配性，该热图在邻近用户接口的用户面部的表面上显示一致的和/或期望的温度。At block 1412, one or more characteristics are identified based on the sensor data (eg, first, second, and/or third sensor data). Identifying the characteristics at block 1412 may include analyzing a given set of sensor data (eg, second sensor data analyzed separately) and/or comparing sets of sensor data (eg, first sensor data compared to third sensor data). Identifying characteristics at block 1412 may include identifying characteristics indicative of a quality of suitability of the user interface. For example, some characteristics may indicate a poor fit of the user interface, while other characteristics may indicate a good fit of the user interface. In one example, a characteristic as a sound indicative of unintentional air leakage may indicate poor fit, while a characteristic as a heat map of the face of a user wearing the user interface may indicate good fit. The surface of the face displays a consistent and/or desired temperature.
可以以合适的方式输出特性，包括作为值(例如，数值或布尔值)、值的集合和/或信号(例如，随时间变化的值的集合)。在一个实例中，与佩戴用户接口时的用户面部的热映射相关联的特性可以被输出为i)是否检测到高于阈值的局部温度变化(例如，温度随时间或跨面部表面上的距离的变化)的布尔值；ii)在围绕用户接口密封的圆周的用户面部上的不同位置处取得的温度值的集合；iii)用户面部的热图像或视频；iv)或i至iii的任何组合，以及其他。Characteristics may be output in a suitable manner, including as a value (eg, a numeric value or a Boolean value), a set of values, and/or a signal (eg, a set of values that changes over time). In one example, characteristics associated with a heat map of the user's face while wearing the user interface may be output as i) whether a local temperature change above a threshold is detected (e.g., temperature over time or across distance on the facial surface) a Boolean value that changes); ii) a collection of temperature values taken at different locations on the user's face around the circumference of the user interface seal; iii) a thermal image or video of the user's face; iv) or any combination of i to iii, And other.
在一些情况下，在框1414处，可以生成与用户接口的适配性相关联的得分。生成适配性得分可以包括分析在框1412处识别的特性并根据这些特性生成得分。在一些情况下，该得分可基于或至少部分地基于使用框1412的一个或多个特性作为输入和/或来自框1402、框1406和/或框1410的传感器数据的计算。In some cases, at block 1414, a score associated with the suitability of the user interface may be generated. Generating the suitability score may include analyzing the characteristics identified at block 1412 and generating a score based on the characteristics. In some cases, the score may be based, or at least in part, based on a calculation using one or more characteristics of block 1412 as input and/or sensor data from block 1402 , block 1406 , and/or block 1410 .
在一些情况下，可以使用机器学习算法使用框1412的一个或多个特性和/或来自框1402、框1406和/或框1410的传感器数据作为输入来计算该得分。这种机器学习算法可以使用与佩戴用户接口的用户的适配性评估的训练集合相关联的特性和/或传感器数据来训练。训练集合中的适配性评估可以基于用户的主观评估、使用其他装备(例如，实验室传感器和装备，诸如配备有专用传感器和/或专用感测装备的用户接口)收集的客观值等。In some cases, the score may be calculated using a machine learning algorithm using one or more characteristics of block 1412 and/or sensor data from block 1402, block 1406, and/or block 1410 as input. Such machine learning algorithms may be trained using characteristics and/or sensor data associated with a training set of fit assessments of users wearing the user interface. Fitness assessments in the training set may be based on subjective assessments by users, objective values collected using other equipment (eg, laboratory sensors and equipment, such as user interfaces equipped with specialized sensors and/or specialized sensing equipment), and the like.
在框1416处，可以生成输出。输出或输出反馈可以包括用于中继关于用户接口的当前适配性的信息的任何合适的输出。该输出可以基于框1412的一个或多个特性；来自框1402、框1406和/或框1410的传感器数据；和/或来自框1414的适配性得分。在一些情况下，该输出可以是在框1414处生成的适配性得分。在一些情况下，该输出可以是来自框1402、框1406和/或框1410的原始或经处理的传感器数据(例如，呈现给用户的热图像或音频记录的一部分)。At block 1416, output can be generated. The output or output feedback may include any suitable output for relaying information about the current suitability of the user interface. The output may be based on one or more characteristics of block 1412; sensor data from block 1402, block 1406, and/or block 1410; and/or the fitness score from block 1414. In some cases, the output may be the fitness score generated at block 1414. In some cases, the output may be raw or processed sensor data from block 1402, block 1406, and/or block 1410 (eg, part of a thermal image or audio recording presented to the user).
在一些情况下，该输出可以是用于被选择来改善用户接口的当前适配性的动作的指令或建议。例如，如果在框1412处识别的特性指示在相对于用户接口的某一位置处存在无意空气泄漏，则该输出可包括对用户接口进行调整(例如，收紧条带)以减少无意空气泄漏的指令，从而改善用户接口的适配性。在一些情况下，对用户接口的适配性的改善可以基于在框1414处生成的当前适配性得分和在框1414的过去或未来例子处生成的过去或未来适配性得分。In some cases, the output may be instructions or suggestions for actions selected to improve the current suitability of the user interface. For example, if the characteristics identified at block 1412 indicate the presence of unintentional air leakage at a certain location relative to the user interface, the output may include adjustments to the user interface (e.g., tightening straps) to reduce unintentional air leakage. instructions to improve the adaptability of the user interface. In some cases, improvements to the suitability of the user interface may be based on the current suitability score generated at block 1414 and past or future suitability scores generated at past or future instances of block 1414 .
在一些情况下，可以使用机器学习算法使用框1412的一个或多个特性；来自框1402、框1406和/或框1410的传感器数据；和/或来自框1414的适配性得分作为输入来选择被选择来改善当前适配性的输出。可以使用与佩戴特定用户接口的用户的适配性评估的训练集合相关联的特性、传感器数据和/或适配性得分来训练这种机器学习算法。训练数据可以包括关于进行的调整的信息，诸如对用户接口进行的调整、对用户面部进行的调整(例如，剃胡须)，和/或不同用户接口的选择。In some cases, a machine learning algorithm may be used to select as input one or more features of block 1412; sensor data from block 1402, block 1406, and/or block 1410; and/or the fitness score from block 1414 Outputs selected to improve current fitness. Such machine learning algorithms may be trained using characteristics, sensor data, and/or fit scores associated with a training set of fit assessments of users wearing a particular user interface. The training data may include information about adjustments made, such as adjustments to the user interface, adjustments to the user's face (eg, shaving), and/or selections of different user interfaces.
在通过将佩戴用户接口之前的传感器数据与佩戴用户接口时的传感器数据进行比较来进行用户接口适配性的评估的实例中，过程1400仅包括框1402、框1404、框1406、框1412和框1414。在另一实例中，其中在用户佩戴用户接口时进行当前适配性的评估，过程1400仅包括框1406、框1412和框1414。在另一实例中，其中通过比较在佩戴用户接口之前和之后用户面部的特性来评估用户接口的当前适配性，过程1400仅包括框1402、框1404、框1408、框1410、框1412和框1414。可以使用其他布置。另外，在一些情况下，呈现为单独的框的各方面可结合到一个或多个其他框中。例如，在一些情况下，在框1414处生成适配性得分作为在框1416处生成输出的一部分而发生。在另一实例中，在一些情况下，过程1400可以从框1412前进到框1416，而不在框1414处生成适配性得分。In an example where the evaluation of user interface fit is performed by comparing sensor data before wearing the user interface to sensor data while the user interface is being worn, process 1400 includes only blocks 1402, 1404, 1406, 1412, and 1414. In another example, in which the assessment of current fit occurs while the user is wearing the user interface, process 1400 includes only blocks 1406, 1412, and 1414. In another example, in which the current fit of the user interface is evaluated by comparing characteristics of the user's face before and after wearing the user interface, process 1400 includes only blocks 1402, 1404, 1408, 1410, 1412, and 1414. Other arrangements can be used. Additionally, in some cases, aspects presented as separate blocks may be combined into one or more other blocks. For example, in some cases, generating the fitness score at block 1414 occurs as part of generating the output at block 1416. In another example, in some cases, process 1400 may proceed from block 1412 to block 1416 without generating a fitness score at block 1414.
图15是描绘根据本公开的一些实施方式的用于评估用户接口的适配性的过程1500的流程图。用户接口可以是任何合适的用户接口，诸如图1中的用户接口100。过程1500可使用控制系统来执行，诸如智能电话234的处理器或服务器(诸如图7中的服务器210)的处理器。Figure 15 is a flowchart depicting a process 1500 for evaluating the suitability of a user interface in accordance with some embodiments of the present disclosure. The user interface may be any suitable user interface, such as user interface 100 in FIG. 1 . Process 1500 may be performed using a control system, such as a processor of smartphone 234 or a processor of a server (such as server 210 in FIG. 7 ).
在框1402处，诸如从用户装置接收与用户接口的当前适配性相关联的传感器数据。在框702处接收的传感器数据可以已经从一个或多个传感器(例如，图4A至图4C中的RPT装置40的一个或多个传感器/换能器4270)收集，该一个或多个传感器/换能器4270中的一个、多于一个，或全部可以结合到用户装置中或联接到用户装置(例如，图7的智能电话234)。传感器数据可以以任何合适的分辨率以相同或不同的频率收集。在一些情况下，检测的频率可以基于使用的传感器。例如，可以以每秒25至60帧(fps)或更高的帧速率获取可见光谱中的图像数据，而可以以10fps或更低的帧速率获取IR频率的热数据。At block 1402, sensor data associated with current suitability of the user interface is received, such as from a user device. The sensor data received at block 702 may have been collected from one or more sensors (eg, one or more sensors/transducers 4270 of RPT device 40 in FIGS. 4A-4C ) that One, more than one, or all of the transducers 4270 may be incorporated into or coupled to a user device (eg, smartphone 234 of Figure 7). Sensor data can be collected at the same or different frequencies at any suitable resolution. In some cases, the frequency of detection may be based on the sensors used. For example, image data in the visible spectrum can be acquired at frame rates of 25 to 60 frames per second (fps) or higher, while thermal data at IR frequencies can be acquired at frame rates of 10 fps or lower.
在一些情况下，在框1502处接收传感器数据可以包括在框1504处校准、调整或稳定传感器数据。校准、调整或稳定传感器数据可以包括对传感器数据进行调整以解决数据中不期望的伪像。校准、调整或稳定传感器数据可以包括使用传感器数据的一部分进行调整。在一个实例中，可以在框1502处稳定图像数据，诸如通过将图像稳定软件应用于图像数据，或者通过应用从智能电话的惯性测量单元(IMU)或子传感器获取的惯性数据。在一些情况下，稳定传感器数据可包括接收与传感器数据的第一部分相关联的图像稳定性信息(例如，与来自可见光谱相机的图像数据相关联的图像稳定性信息)并将该稳定性信息应用于传感器数据的第二部分(例如，来自另一传感器的传感器数据，诸如来自IR传感器的热数据)。在一个实例中，与可见光谱相机数据的稳定性相关联的图像稳定性信息(例如，如经由图像稳定软件和/或惯性数据获得的)可以应用于来自IR传感器的热数据，因此允许在当单独使用热数据时可能出现的情况之外稳定热数据。In some cases, receiving sensor data at block 1502 may include calibrating, adjusting, or stabilizing the sensor data at block 1504 . Calibrating, adjusting, or stabilizing sensor data may include making adjustments to the sensor data to account for undesirable artifacts in the data. Calibrating, adjusting, or stabilizing sensor data may include using a portion of the sensor data to make adjustments. In one example, the image data may be stabilized at block 1502, such as by applying image stabilization software to the image data, or by applying inertial data obtained from an inertial measurement unit (IMU) or sub-sensor of the smartphone. In some cases, stabilizing the sensor data may include receiving image stabilization information associated with the first portion of the sensor data (eg, image stabilization information associated with image data from a visible spectrum camera) and applying the stabilization information to a second portion of sensor data (eg, sensor data from another sensor, such as thermal data from an IR sensor). In one example, image stability information associated with the stability of visible spectrum camera data (eg, as obtained via image stabilization software and/or inertial data) can be applied to thermal data from the IR sensor, thus allowing Stabilizes thermal data beyond what might occur when using thermal data alone.
校准可以通过获取已知或标称对象或事件的传感器数据而发生。例如，图像数据中的曝光和/或颜色温度的校准可以通过首先从校准表面(例如，已知颜色的表面，诸如白平衡卡)收集参考图像数据，然后使用该参考图像数据来调整获取图像数据的传感器的设置和/或调整图像数据本身来实现。Calibration can occur by acquiring sensor data from known or nominal objects or events. For example, calibration of exposure and/or color temperature in image data may be accomplished by first collecting reference image data from a calibration surface (e.g., a surface of known color, such as a white balance card) and then using that reference image data to adjust the acquired image data. This is achieved by setting up the sensor and/or adjusting the image data itself.
调整可以通过使用传感器数据的一部分来通知对其他传感器数据进行的调整而发生。例如，热成像器(例如，IR传感器)可以收集热数据以生成用户面部的热图。热图可以识别用户面部上的各个位置处的局部温度，以及周围环境中的一些表面，诸如用户后面的表面。在这种实例中，热数据可以指示用户后面的表面是19℃。然而，从单独的温度传感器收集的环境温度数据可指示用户后面的表面和/或环境室温更接近21℃。因此，该系统可以自动调整从热成像器获取的热数据，使得对于用户后面的表面感测的温度等于由单独的温度传感器测量的温度(例如，21℃)。因此，这种调整还可以延续到用户面部上的各个位置处的局部温度值。Adjustments can occur by using a portion of the sensor data to inform adjustments to other sensor data. For example, a thermal imager (eg, IR sensor) can collect thermal data to generate a heat map of the user's face. Heat maps can identify local temperatures at various locations on a user's face, as well as some surfaces in the surrounding environment, such as surfaces behind the user. In such an example, the thermal data may indicate that the surface behind the user is 19°C. However, ambient temperature data collected from a separate temperature sensor may indicate that the surface behind the user and/or the ambient room temperature is closer to 21°C. Therefore, the system can automatically adjust the thermal data acquired from the thermal imager so that the temperature sensed for the surface behind the user is equal to the temperature measured by a separate temperature sensor (eg, 21°C). Therefore, this adjustment can also be carried over to the local temperature values at various locations on the user's face.
在另一实例中，来自一个或多个传感器的传感器数据可用于与来自一个或多个其他传感器的传感器数据关联并对来自一个或多个其他传感器的传感器数据进行协调。例如，来自可见光谱相机的图像数据可以与来自IR传感器的热映射数据关联。在这种实例中，可以将图像数据中的某些检测到的特征(例如，眼睛、耳朵、鼻、嘴、用户接口通气孔等)与热映射数据中的类似的检测到的特征进行比较。因此，如果图像数据和热映射数据不是以相同的比例和视场收集的，数据仍然可以一起关联。例如，可以调整热映射数据的所有像素(例如，在X方向和/或Y方向上拉伸)，使得在图像数据中检测到的特征的位置与热映射数据中的相关特征的位置相匹配。In another example, sensor data from one or more sensors may be used to correlate and coordinate sensor data from one or more other sensors. For example, image data from a visible spectrum camera can be correlated with heat mapping data from an IR sensor. In such instances, certain detected features in the image data (eg, eyes, ears, nose, mouth, user interface vents, etc.) may be compared to similar detected features in the heat map data. Therefore, if the image data and thermal mapping data are not collected at the same scale and field of view, the data can still be correlated together. For example, all pixels of the heat map data can be adjusted (eg, stretched in the X direction and/or Y direction) so that the location of the feature detected in the image data matches the location of the associated feature in the heat map data.
在一些情况下，调整传感器数据可以包括利用与i)用户装置的移动，ii)用户装置的固有噪声，iii)用户的呼吸噪声，iv)用户的说话(或其他发声)噪声，v)环境照明的变化，vi)检测到的投射在用户的面部上的瞬态阴影，vii)检测到的投射在用户的面部上的瞬态有色光，或viii)i至vii的任何组合有关的传感器数据的多个部分来调整传感器数据。In some cases, adjusting the sensor data may include utilizing information related to i) movement of the user device, ii) inherent noise of the user device, iii) breathing noise of the user, iv) speaking (or other vocalization) noise of the user, v) ambient lighting changes in sensor data related to vi) a detected transient shadow cast on the user's face, vii) a detected transient colored light cast on the user's face, or viii) any combination of i to vii Multiple sections to adjust sensor data.
可使用其他技术来基于传感器数据的一部分和/或其他数据(例如，历史传感器数据、从未联接到系统的传感器获取的传感器数据等)来校准、调整或稳定或以其他方式修改传感器数据。Other techniques may be used to calibrate, adjust or stabilize or otherwise modify the sensor data based on portions of the sensor data and/or other data (e.g., historical sensor data, sensor data obtained from sensors not coupled to the system, etc.).
在一些情况下，在框1506处，可以提供感测反馈作为在框1502处接收传感器数据的一部分。提供感测反馈可以包括在框1502处向用户呈现关于接收传感器数据的过程的反馈。在第一实例中，感测反馈可以包括显示器上的文本或图像，该文本或图像指示关于正在进行的传感器数据收集的指令。例如，感测反馈可以采取指定叠加在面向用户的相机的实况相机馈送上的屏幕的分区的轮廓线或其他标记的形式，在这种情况下，指导用户将他们的面部保持在屏幕的轮廓线或分区内。In some cases, at block 1506 , sensory feedback may be provided as part of receiving the sensor data at block 1502 . Providing sensory feedback may include presenting feedback to the user regarding the process of receiving sensor data at block 1502 . In a first example, sensory feedback may include text or images on a display indicating instructions regarding ongoing sensor data collection. For example, sensory feedback may take the form of contours or other markings that specify portions of the screen superimposed on the live camera feed of the user-facing camera, in which case the user is instructed to keep their face within the contours of the screen or within the zone.
在另一实例中，在框1502处接收传感器数据可以发生一段设定的持续时间或直到成功地获得了某些传感器数据。在这种情况下，用户可能需要将用户装置保持在特定取向。一旦已经过去了持续时间或者已经获得了某些传感器数据，用户装置就可以呈现感测反馈1506，以指示用户可以停止将用户装置保持在特定取向(例如，用户装置的显示器背向用户)。感测反馈可以是视觉和/或非视觉提示(例如，刺激，诸如提示、指令、通知等)的形式。在一些情况下，使用非视觉提示(例如，音频提示或触觉反馈)可能尤其有用，诸如如果用户装置的显示器当前对用户不可见。In another example, receiving sensor data at block 1502 may occur for a set duration or until certain sensor data is successfully obtained. In this case, the user may need to hold the user device in a specific orientation. Once the duration has elapsed or certain sensor data has been obtained, the user device may present sensory feedback 1506 to indicate that the user may cease maintaining the user device in a particular orientation (eg, with the user device's display facing away from the user). Sensory feedback may be in the form of visual and/or non-visual cues (eg, stimuli such as prompts, instructions, notifications, etc.). Using non-visual cues (eg, audio cues or tactile feedback) may be particularly useful in some situations, such as if the display of the user's device is not currently visible to the user.
在一些情况下，在框1506处提供感测反馈可以包括向用户呈现指令以执行某些动作来引起可由一个或多个传感器检测到的效果。例如，可以指导用户屏住呼吸达一定持续时间、对着相机微笑、咀嚼、打哈欠、说话、戴上和/或移除用户接口等。在框1514处，可检测的效果可用于检测特性。在一个实例中，可检测的效果可以是当用户说话、咀嚼或打哈欠时用户接口相对于用户面部的移动量。在这种实例中，用户接口的过度移动可能指示不良适配性。在一些情况下，在框1502处接收传感器数据可以包括接收与在框1506处指导的用户完成动作相关联的完成信号。完成信号检测的实例包括感测按钮按压(例如，用户按压“完成”按钮)以及自动检测动作的完成(例如，经由相机数据)。In some cases, providing sensory feedback at block 1506 may include presenting instructions to the user to perform certain actions to cause an effect detectable by one or more sensors. For example, the user can be instructed to hold their breath for a certain duration, smile at the camera, chew, yawn, talk, put on and/or remove the user interface, etc. At block 1514, detectable effects can be used to detect properties. In one example, the detectable effect may be the amount of movement of the user interface relative to the user's face when the user talks, chews, or yawns. In such instances, excessive movement of the user interface may indicate poor fit. In some cases, receiving sensor data at block 1502 may include receiving a completion signal associated with the user's completion action directed at block 1506 . Examples of completion signal detection include sensing button presses (eg, a user presses a "Done" button) and automatically detecting completion of an action (eg, via camera data).
在一些情况下，在框1506处提供感测反馈可以包括为用户提供移动到期望位置(例如，在室内移动或移动到良好照明的房间)、调整环境(例如，打开或关闭房间中的灯)和/或调整其取向或姿势(例如，端坐)的指令。In some cases, providing sensory feedback at block 1506 may include providing the user with options to move to a desired location (e.g., move indoors or to a well-lit room), adjust the environment (e.g., turn lights in the room on or off) and/or instructions to adjust their orientation or posture (e.g., sit upright).
在一些情况下，在框1502处接收传感器数据可以包括在框1508处控制呼吸系统。在框1508处控制呼吸治疗系统可以包括将控制信号发送到联接到用户接口的呼吸治疗装置。当呼吸治疗装置接收到控制信号时，该控制信号可以使呼吸治疗装置调整参数或采取某些动作。例如，控制信号可以使呼吸治疗装置打开和/或关闭；以给定压力或预设压力模式供应空气；激活和/或停用加热器和/或加湿器；和/或采取任何其他合适的动作。In some cases, receiving sensor data at block 1502 may include controlling the respiratory system at block 1508 . Controlling the respiratory therapy system at block 1508 may include sending a control signal to a respiratory therapy device coupled to the user interface. When the respiratory treatment device receives a control signal, the control signal may cause the respiratory treatment device to adjust parameters or take certain actions. For example, control signals may cause a respiratory therapy device to turn on and/or turn off; supply air at a given pressure or preset pressure pattern; activate and/or deactivate a heater and/or humidifier; and/or take any other suitable action .
在框1510处，可以使用传感器数据生成面部映射。面部映射可以使用任何合适的传感器数据来生成，诸如测距数据(例如，来自LiDAR传感器或IR传感器)、图像数据(例如，来自相机)和/或热数据(例如，来自IR传感器)。面部映射可以识别用户面部的一个或多个特征，诸如眼睛、鼻、嘴、耳朵、虹膜等。面部映射可以包括测量识别的特征的任何组合之间的距离。得到的面部映射可以是二维或三维面部映射。或者，面部映射和结果数据可以从存储的数据中获得，该存储的数据是从如上面参考图8A至图8C解释的那样执行的面部扫描中收集的。At block 1510, a facial map may be generated using the sensor data. The facial map may be generated using any suitable sensor data, such as odometry data (eg, from a LiDAR sensor or IR sensor), image data (eg, from a camera), and/or thermal data (eg, from an IR sensor). Facial mapping can identify one or more features of a user's face, such as eyes, nose, mouth, ears, iris, etc. Facial mapping can include measuring distances between any combination of identified features. The resulting facial map can be a two-dimensional or three-dimensional facial map. Alternatively, the facial mapping and resulting data may be obtained from stored data collected from facial scans performed as explained above with reference to Figures 8A-8C.
在一些情况下，面部映射是轮廓图，指示与用户面部相关联的轮廓和高度。在一些情况下，面部映射是热图，指示用户面部上不同位置处的局部温度。In some cases, the face map is a contour map indicating the contours and height associated with the user's face. In some cases, the face map is a heat map indicating local temperatures at different locations on the user's face.
在一些情况下，在框1510处生成面部映射可以包括识别第一个体和一个或多个附加个体。在此类情况下，生成面部映射可以包括选择第一个体(例如，基于最接近一个或多个传感器或用户装置的第一个体，基于与先前记录的图像或第一用户的特性的比较，或者基于其他此类分析)，并且使用在第一个体的面部上检测到的一个或多个特征继续进行面部映射生成。In some cases, generating the facial map at block 1510 may include identifying the first individual and one or more additional individuals. In such cases, generating the facial map may include selecting the first individual (e.g., based on the first individual being closest to one or more sensors or user devices, based on comparison with previously recorded images or characteristics of the first user) , or based on other such analysis), and continues facial map generation using the one or more features detected on the first individual's face.
在一些情况下，在可选框1512处，可使用传感器数据生成用户接口映射。用户接口映射可以使用任何合适的传感器数据来生成，诸如测距数据(例如，来自LiDAR传感器或IR传感器)、图像数据(例如，来自相机)和/或热数据(例如，来自IR传感器)。用户接口映射可以识别用户接口的一个或多个特征，诸如通气口、轮廓、导管、导管连接、条带等。用户接口映射可以包括测量识别的特征的任何组合之间的距离。得到的用户接口映射可以是二维或三维用户接口映射。In some cases, at optional block 1512, the sensor data may be used to generate a user interface map. The user interface map may be generated using any suitable sensor data, such as odometry data (eg, from a LiDAR sensor or IR sensor), image data (eg, from a camera), and/or thermal data (eg, from an IR sensor). The user interface map may identify one or more features of the user interface, such as vents, contours, conduits, conduit connections, strips, etc. User interface mapping may include measuring distances between any combination of identified features. The resulting user interface map may be a two-dimensional or three-dimensional user interface map.
在一些情况下，在框1510处生成面部映射可以包括在框1512处生成用户接口映射。In some cases, generating the facial map at block 1510 may include generating a user interface map at block 1512 .
在框1514处，使用来自框1502的传感器数据和来自框1510的面部映射来识别与当前适配性相关联的一个或多个特性。在一些情况下，在框1514处识别特性可以包括使用在框1512处生成的接口映射。At block 1514 , one or more characteristics associated with the current fit are identified using the sensor data from block 1502 and the facial mapping from block 1510 . In some cases, identifying the characteristics at block 1514 may include using the interface map generated at block 1512 .
可以识别任何合适的特性。这些特性可以包括用户面部的特性、用户面部与用户接口之间的交互的特性、用户接口的特性以及环境的特性。在一些情况下，特性可以是用户面部、用户接口、用户面部和用户接口之间的交互，或环境的可识别方面，该可识别方面可以根据传感器数据检测，并且该可识别方面具有用于确定用户接口的适配性的质量的检验值。Any suitable properties can be identified. These characteristics may include characteristics of the user's face, characteristics of the interaction between the user's face and the user interface, characteristics of the user interface, and characteristics of the environment. In some cases, the characteristic may be the user's face, the user interface, the interaction between the user's face and the user interface, or an identifiable aspect of the environment that can be detected based on sensor data and that has the ability to determine A test value for the quality of user interface suitability.
在一些情况下，特性可以与位置相关联，尽管不必总是这种情况。与位置相关联的特性可以与面部映射和/或用户接口映射上的位置相关联或参考面部映射和/或用户接口映射的位置相关联。例如，示例特性可以是指示无意空气泄漏的音频信号(例如，具有与无意空气泄漏相关联的特性频率档案的音频信号)或无意空气泄漏本身。在一些情况下，该特性可以单独使用(例如，可以使用无意空气泄漏的存在或不存在，诸如以生成适配性得分)，或者和与该特性相关联的位置信息组合使用。在这种实例中，无意空气泄漏可以检测为在用户面部上的某一位置处(例如，如图12中可见的鼻和左脸颊之间)，在这种情况下，位置信息可以指示与无意空气泄漏在用户面部上存在的位置关联的面部映射或用户接口映射上的位置。与用户接口一起添加位置信息可便于提供有用的信息，诸如更准确的适配性得分和/或更准确的指令以改善适配性。In some cases, properties can be associated with locations, although this need not always be the case. Properties associated with location may be associated with or reference a location on the facial map and/or user interface map. For example, an example characteristic may be an audio signal indicative of an unintentional air leak (eg, an audio signal having a characteristic frequency profile associated with the unintentional air leak) or the unintentional air leak itself. In some cases, this characteristic may be used alone (eg, the presence or absence of inadvertent air leakage may be used, such as to generate a fitness score), or in combination with location information associated with the characteristic. In such an example, the unintentional air leak may be detected at a certain location on the user's face (eg, between the nose and left cheek as seen in Figure 12), in which case the location information may indicate that the leakage is related to the unintentional air leakage. The location on the user's face where the air leak exists is associated with a location on the face map or the user interface map. Adding location information along with the user interface can facilitate providing useful information, such as more accurate fitness scores and/or more accurate instructions to improve fitness.
在一些情况下，可以预先确定可用特性的集合。在此类情况下，在框1514处识别特性可以包括分析传感器数据和/或面部映射以确定检测到可用特性的集合中的哪一个(如果有的话)。例如，可用特性的集合可以包括用户的面部上的局部温度回弹、用户的面部上的局部颜色回弹，以及用户接口上的局部温度。在这种实例中，如果传感器数据不包括热数据(例如，如果没有IR传感器或温度传感器可用)，则可以确定的该列表中的唯一特性是局部颜色回弹，该局部颜色回弹可以从由相机收集的图像数据中检测到。在另一实例中，如果存在足够的热数据，则可另外检测用户接口的局部温度回弹和局部温度。In some cases, the set of available features may be predetermined. In such cases, identifying the characteristics at block 1514 may include analyzing sensor data and/or facial mapping to determine which, if any, of the set of available characteristics were detected. For example, the set of available properties may include local temperature rebound on the user's face, local color rebound on the user's face, and local temperature on the user interface. In such an instance, if the sensor data does not include thermal data (e.g., if no IR sensor or temperature sensor is available), the only characteristic in this list that can be determined is local color rebound, which can be obtained from Detected in the image data collected by the camera. In another example, if sufficient thermal data is present, local temperature rebound and local temperature of the user interface may be additionally detected.
在一些情况下，特性可以是有益特性或有害特性。有益特性可以是与用户接口的良好适配性相关联的特性。例如，作为呈用户接口的密封形状的用户的面部上的局部轮廓的特性可以指示用户接口保持与用户面部的良好适配性。因此，这种特性的存在或更大的存在可能是有益的。相反，有害特性可能与用户接口的不良适配性相关联。例如，作为用户面部一分区上的局部温度变化的特性可以指示冷空气在用户面部的该分区上流动，从而指示与不良适配性相关联的无意空气泄漏。因此，这种特性的存在或更大的存在可能是有害的。In some cases, properties may be beneficial or detrimental. Beneficial properties may be properties associated with good adaptability of the user interface. For example, the characteristic of a local contour on a user's face as being in a sealed shape of the user interface may indicate that the user interface maintains a good fit with the user's face. Therefore, the presence or greater presence of this property may be beneficial. Conversely, harmful properties may be associated with poor fit of the user interface. For example, characteristics as localized temperature changes over a region of the user's face may indicate that cold air is flowing over that region of the user's face, thereby indicating inadvertent air leakage associated with poor fit. Therefore, the presence or greater presence of this property can be detrimental.
一个示例特性是用户的面部上的局部温度。该特性可以是在用户的面部上检测到的温度，该检测到的温度可以与在该相同位置(例如，用户佩戴用户接口的先前时间)处先前检测到的温度或在邻近位置处检测到的当前温度进行比较。例如，如果在用户接口的密封附近检测到冷点，但该冷点被较暖的温度包围，则该冷点可指示无意空气泄漏。An example characteristic is the local temperature on the user's face. The characteristic may be a temperature detected on the user's face, which may be the same as a temperature previously detected at the same location (e.g., a previous time the user wore the user interface) or a temperature detected at a nearby location. Compare the current temperature. For example, if a cold spot is detected near the seal of a user interface but is surrounded by warmer temperatures, the cold spot may indicate an unintentional air leak.
另一示例特性是用户的面部上的局部温度回弹。局部温度回弹可以包括在某一位置(例如，面部映射上的某一位置)处在一段时间内温度的变化。局部温度回弹可以跟随瞬态事件，诸如用户接口瞬态事件(例如，用户接口的移除)、用户瞬态事件(例如，从温暖房间移动到较冷房间)、呼吸治疗系统瞬态事件(例如，接合呼吸治疗系统的加热器，诸如流量发生器的加热器、加湿器的加热器和/或导管的加热器)，或另一瞬态事件。例如，在移除用户接口之后在相对于面部映射的某些位置处检测到较长的温度回弹时间可以指示不良适配性。测量的特性(例如，温度、颜色、轮廓等)的“回弹”可以包括在诸如戴上、脱卸或调整用户接口，启动或停止来自RPT装置的加压空气的流动的瞬态事件或例如产生测量的特性随时间的变化的另一事件之后测量的特性的变化。Another example feature is localized temperature rebound on the user's face. Local temperature rebound may include changes in temperature over time at a certain location (eg, a certain location on a facial map). Local temperature rebound can follow transient events, such as user interface transient events (e.g., removal of a user interface), user transient events (e.g., moving from a warm room to a cooler room), respiratory therapy system transient events (e.g., movement from a warm room to a cooler room) For example, engaging a heater of a respiratory therapy system, such as a heater of a flow generator, a heater of a humidifier, and/or a heater of a catheter), or another transient event. For example, detecting long temperature rebound times at certain locations relative to the face map after removing the user interface may indicate poor fit. "Bounceback" of measured properties (e.g., temperature, color, contour, etc.) may include transient events such as donning, doffing, or adjusting the user interface, initiating or stopping the flow of pressurized air from the RPT device, or e.g. A change in a measured property over time A change in a measured property following another event.
另一示例特性是用户的面部上的局部颜色。该特性可以是在用户的面部上检测到的颜色，该颜色可以与在该相同位置(例如，用户佩戴用户接口的先前时间)处先前检测到的颜色或在邻近位置处检测到的当前颜色进行比较。例如，如果在用户接口的密封附近检测到较红的部位，但是该较红的部位被较白的颜色包围，则该较红的部位可以指示无意空气泄漏(例如，由于密封没有太多地压靠在用户面部和/或由于来自流动的空气的刺激)。Another example feature is local color on the user's face. The characteristic may be a color detected on the user's face, which color may be compared to a previously detected color at that same location (e.g., a previous time the user wore the user interface) or a current color detected at a nearby location. Compare. For example, if a redder spot is detected near a seal of a user interface, but is surrounded by whiter colors, the redder spot could indicate an unintentional air leak (e.g., due to the seal not compressing as much). against the user's face and/or due to irritation from moving air).
另一示例特性是用户的面部上的局部颜色回弹。局部颜色回弹可以包括在某一位置(例如，面部映射上的某一位置)处在一段时间内颜色的变化。局部颜色回弹可以跟随瞬态事件，诸如用户接口瞬态事件(例如，用户接口的移除)、用户瞬态事件(例如，从温暖房间移动到较冷房间)、呼吸治疗系统瞬态事件(例如，打开或关闭呼吸治疗装置)，或另一瞬态事件。例如，在移除用户接口之后在相对于面部映射的某些位置处检测到较长的颜色回弹时间可以指示良好适配性。Another example feature is localized color bounce on the user's face. Local color rebound may include changes in color over time at a certain location (eg, a certain location on a facial map). Local color rebound can follow transient events, such as user interface transient events (e.g., removal of a user interface), user transient events (e.g., moving from a warm room to a cooler room), respiratory therapy system transient events (e.g., moving from a warm room to a cooler room) For example, turning a respiratory therapy device on or off), or another transient event. For example, detecting long color bounce times at certain locations relative to the face map after removing the user interface may indicate good fit.
另一示例特性是用户的面部上的局部轮廓。该特性可以是在用户的面部上检测到的轮廓，该轮廓可以与在该相同位置(例如，用户佩戴用户接口的先前时间)处先前检测到的轮廓或在邻近位置处检测到的当前轮廓进行比较。例如，如果在用户接口的整个密封周围的用户皮肤上检测到一定量的压痕，则该压痕可指示强密封和良好适配性。Another example feature is local contours on the user's face. The feature may be a profile detected on the user's face, which profile may be compared to a previously detected profile at the same location (e.g., a previous time the user wore the user interface) or a current profile detected at a nearby location. Compare. For example, if a certain amount of indentation is detected on the user's skin around the entire seal of the user interface, the indentation may indicate a strong seal and good fit.
另一示例特性是用户的面部上的局部轮廓回弹。局部轮廓回弹可以包括在某一位置(例如，面部映射上的某一位置)处在一段时间内轮廓的变化。局部轮廓回弹可以跟随瞬态事件，诸如用户接口瞬态事件(例如，用户接口的移除)、用户瞬态事件(例如，从温暖房间移动到较冷房间)、呼吸治疗系统瞬态事件(例如，打开或关闭呼吸治疗装置)，或另一瞬态事件。例如，在移除用户接口之后在相对于面部映射的某些位置处检测到较长的轮廓回弹时间可以指示良好适配性。Another example feature is local contour springback on the user's face. Local contour rebound may include changes in contour over time at a certain location (eg, a certain location on a facial map). Local contour rebound can follow transient events, such as user interface transient events (e.g., removal of a user interface), user transient events (e.g., moving from a warm room to a cooler room), respiratory therapy system transient events (e.g., moving from a warm room to a cooler room) For example, turning a respiratory therapy device on or off), or another transient event. For example, detecting long contour rebound times at certain locations relative to the face map after removing the user interface may indicate good fit.
另一示例特性是用户接口上的局部轮廓。该特性可以是在用户接口上(例如，在用户接口的一部分上，诸如用户接口的密封)检测到的轮廓，该轮廓可以与在该相同位置(例如，在用户接口被佩戴的先前时间)处先前检测到的轮廓或在用户接口上的其他位置处检测到的当前轮廓进行比较。例如，如果在用户接口的密封上检测到一定量的压痕，则该压痕可指示强密封和良好适配性。Another example feature is a partial outline on the user interface. The characteristic may be a profile detected on the user interface (e.g., on a portion of the user interface, such as a seal of the user interface) that may be the same as at the same location (e.g., at a previous time the user interface was worn) Comparisons are made with previously detected contours or with the current contour detected elsewhere on the user interface. For example, if a certain amount of indentation is detected on the seal of a user interface, the indentation can indicate a strong seal and good fit.
另一示例特性是用户接口上的局部轮廓回弹。局部轮廓回弹可以包括在用户接口上的某一位置(例如，用户接口映射上的某一位置)处在一段时间内轮廓的变化。局部轮廓回弹可以跟随瞬态事件，诸如用户接口瞬态事件(例如，用户接口的移除)、用户瞬态事件(例如，从温暖房间移动到较冷房间)、呼吸治疗系统瞬态事件(例如，打开或关闭呼吸治疗装置)，或另一瞬态事件。例如，在用户接口的密封上的某些位置处检测到较长的轮廓回弹时间可指示不良适配性和/或失败的密封(例如，失败的密封可能不会很快回弹)。Another example feature is local contour springback on the user interface. Local contour rebound may include changes in the contour over time at a certain location on the user interface (eg, a certain location on the user interface map). Local contour rebound can follow transient events, such as user interface transient events (e.g., removal of a user interface), user transient events (e.g., moving from a warm room to a cooler room), respiratory therapy system transient events (e.g., moving from a warm room to a cooler room) For example, turning a respiratory therapy device on or off), or another transient event. For example, detecting long profile rebound times at certain locations on the seal of the user interface may indicate poor fit and/or a failed seal (eg, a failed seal may not rebound quickly).
另一示例特性是用户接口上的局部温度。该特性可以是在用户接口上的某个位置(例如，在用户接口的一部分上，诸如密封)处检测到的温度，该温度可以与在该相同位置(例如，用户接口被佩戴的先前时间)处先前检测到的温度或在用户接口上的其他位置处检测到的当前温度进行比较。例如，如果在用户接口的密封上的一位置处检测到冷点，但用户接口的其他部分被检测为较暖，则该冷点可指示无意空气泄漏。在另一实例中，用户接口或导管的一部分加热到给定温度花费的时间长度可以指示良好或不良适配性。Another example characteristic is local temperature on the user interface. The characteristic may be a temperature detected at a location on the user interface (e.g., on a portion of the user interface, such as a seal) that may be the same temperature at that same location (e.g., a previous time the user interface was worn) Compare this to a previously detected temperature or the current temperature detected elsewhere on the user interface. For example, if a cold spot is detected at one location on the seal of the user interface, but other parts of the user interface are detected to be warmer, the cold spot may indicate an unintentional air leak. In another example, the length of time it takes for a portion of the user interface or conduit to heat to a given temperature may indicate good or poor fit.
另一示例特性是用户接口相对于用户的面部的一个或多个特征的垂直位置。用户接口相对于用户的面部的一个或多个特征的垂直位置可以基于面部映射和传感器数据和/或用户接口映射。在一个实例中，如果用户接口或用户接口的检测到的特征检测为相对于用户面部的一个或多个特征(例如下巴、嘴和/或鼻)过高或过低，则这可能指示不良适配性(例如，条带可拉动用户接口过高或过低)。Another example characteristic is the vertical position of the user interface relative to one or more features of the user's face. The vertical position of the user interface relative to one or more features of the user's face may be based on facial mapping and sensor data and/or user interface mapping. In one example, if the user interface or a detected feature of the user interface is detected to be too high or too low relative to one or more features of the user's face, such as the chin, mouth, and/or nose, this may indicate poor fitness. Matchability (for example, a strip can pull the user interface too high or too low).
另一示例特性是用户接口相对于用户的面部的一个或多个特征的水平位置。用户接口相对于用户的面部的一个或多个特征的水平位置可以基于面部映射和传感器数据和/或用户接口映射。在一个实例中，如果用户接口或用户接口的检测到的特征检测为离用户面部的一侧或另一侧太远，则这可能指示不良适配性(例如，条带可能将用户接口拉动得离用户右侧或左侧太多)。Another example characteristic is the horizontal position of the user interface relative to one or more features of the user's face. The horizontal position of the user interface relative to one or more features of the user's face may be based on facial mapping and sensor data and/or user interface mapping. In one example, if the user interface or a detected feature of the user interface is detected to be too far from one side or the other of the user's face, this may indicate a poor fit (e.g., a band may pull the user interface too far) too far to the user's right or left).
另一示例特性是用户接口相对于用户的面部的一个或多个特征的旋转取向。旋转取向可以是用户接口相对于用户面部绕从用户面部向外延伸的旋转轴旋转多远的量度，该旋转轴诸如是从面部沿前或腹侧方向延伸的旋转轴。用户接口相对于用户的面部的一个或多个特征的旋转取向可以基于面部映射和传感器数据和/或用户接口映射。在一个实例中，如果用户接口或用户接口的检测到的特征检测为相对于用户面部的一个或多个特征旋转了过高的程度，则这可能指示不良适配性(例如，条带可能正在用户面部上扭转用户接口)。Another example characteristic is the rotational orientation of the user interface relative to one or more features of the user's face. Rotational orientation may be a measure of how far the user interface is rotated relative to the user's face about an axis of rotation extending outwardly from the user's face, such as an axis of rotation extending in an anterior or ventral direction from the face. The rotational orientation of the user interface relative to one or more features of the user's face may be based on facial mapping and sensor data and/or user interface mapping. In one example, if the user interface or a detected feature of the user interface is detected to be rotated to an excessive degree relative to one or more features of the user's face, this may indicate poor fit (e.g., a band may be Twisting the user interface on the user's face).
另一示例特性是用户接口的识别的特征相对于用户的面部的一个或多个特征之间的距离。该距离可以基于面部映射和传感器数据和/或用户接口映射。在一个实例中，如果用户接口的检测到的特征(例如，通气口)检测为与用户面部的检测到的特征(例如，鼻梁)偏移太远，则这可能指示不良适配性。该距离可以在一维、二维或三维中测量。在一个实例中，太宽松地适配在用户面部上的用户接口可以具有通气口，该通气口定位成与用户面部的表面相距相对大的距离，这可以指示不良适配性。在这种情况下，通气口和用户面部的特征之间的距离的测量可以指示不良适配性，这可以通过收紧用户接口的条带来校正。Another example characteristic is the distance between an identified feature of the user interface relative to one or more features of the user's face. The distance may be based on facial mapping and sensor data and/or user interface mapping. In one example, if a detected feature of the user interface (eg, a vent) is detected as being offset too far from a detected feature of the user's face (eg, the bridge of the nose), this may indicate a poor fit. The distance can be measured in one, two or three dimensions. In one example, a user interface that fits too loosely on the user's face may have a vent positioned a relatively large distance from the surface of the user's face, which may be indicative of a poor fit. In this case, measurement of the distance between the vent and features of the user's face can indicate a poor fit, which can be corrected by tightening the straps of the user interface.
在另一实例中，在框1514处识别泄漏特性可包括基于来自框1502的接收的传感器数据确定用户的呼吸模式，基于来自框1502的接收的传感器数据和来自框1510的面部映射确定与用户的面部相关联的热模式，然后使用该呼吸模式和该热模式生成指示有意通气口泄漏和无意密封泄漏之间的平衡的泄漏特性信号。例如，使用该呼吸模式和该热模式，可以生成有意通气口泄漏信号，该信号指示有意通气口泄漏的实例，并且可选地指示有意通气口泄漏的强度。可以针对无意密封泄漏生成类似的无意密封泄漏信号。泄漏特性信号可以是无意密封泄漏信号与有意密封泄漏信号之间的比率。In another example, identifying leakage characteristics at block 1514 may include determining the user's breathing pattern based on the received sensor data from block 1502 , determining the user's breathing pattern based on the received sensor data from block 1502 and the facial mapping from block 1510 . The thermal pattern associated with the face is then used to generate a leak characteristic signal indicating the balance between intentional vent leakage and unintentional seal leakage using the breathing pattern and the thermal pattern. For example, using the breathing pattern and the thermal pattern, an intentional vent leak signal can be generated that indicates an instance of intentional vent leak and, optionally, the intensity of the intentional vent leak. A similar unintentional seal leakage signal can be generated for unintentional seal leakage. The leakage characteristic signal may be a ratio between an unintentional seal leakage signal and an intentional seal leakage signal.
在一些情况下，在框1514处识别特性可以包括在框1516处识别并确认潜在的特性。识别并确认潜在的特性可以包括使用传感器数据的第一集合来识别该特性，然后使用传感器数据的第二集合来确认该特性。传感器数据的该第一集合和传感器数据的该第二集合可以从相同的传感器但是在不同的时间收集，或者可以从不同的传感器收集。例如，在不同时间从相同传感器收集可包括在用户佩戴用户接口时根据热数据识别潜在的无意空气泄漏(例如，检测用户面部的表面温度在围绕用户接口的周边的分区上的局部变化)，然后使用在用户已移除用户接口之后获取的热数据来确认该无意空气泄漏(例如，检测在一段持续时间内用户面部在特定分区处的用户面部的表面温度缺乏变化，诸如当血液冲回到其他位置处的先前压缩的组织中时，但不邻近潜在的空气泄漏)。In some cases, identifying properties at block 1514 may include identifying and validating potential properties at block 1516 . Identifying and confirming a potential characteristic may include using a first set of sensor data to identify the characteristic and then using a second set of sensor data to confirm the characteristic. The first set of sensor data and the second set of sensor data may be collected from the same sensor but at different times, or may be collected from different sensors. For example, collecting from the same sensor at different times may include identifying potential inadvertent air leaks based on thermal data while the user is wearing the user interface (e.g., detecting local changes in the surface temperature of the user's face over a zone around the perimeter of the user interface) and then Confirm this unintentional air leak using thermal data acquired after the user has removed the user interface (e.g., detecting a lack of change in the surface temperature of the user's face at specific partitions over a sustained period of time, such as when blood rushes back to other location within previously compressed tissue but not adjacent to potential air leaks).
在另一实例中，收集来自不同传感器的传感器数据以识别并确认潜在的特性可包括使用在用户佩戴用户接口时收集的热数据来识别潜在的无意空气泄漏，然后使用同时收集的音频数据来确认无意空气泄漏(例如，通过检测指示无意空气泄漏的特性音频或声学信号，该无意空气泄漏与同时在热图像中检测到潜在的无意空气泄漏同时发生)。In another example, collecting sensor data from different sensors to identify and confirm potential characteristics may include using thermal data collected while the user is wearing the user interface to identify potential inadvertent air leaks, and then using audio data collected at the same time to confirm Unintentional air leakage (e.g., by detecting a characteristic audio or acoustic signal indicating an unintentional air leakage that occurs simultaneously with a potential unintentional air leakage being detected in the thermal image).
在一些情况下，可以在框1520处从呼吸装置接收附加传感器数据，并在框1514处将该附加传感器数据用于识别特性。来自呼吸治疗装置的附加传感器数据可以包括从呼吸治疗系统(诸如图1中的呼吸治疗系统)获取的数据。此类附加传感器数据可以包括诸如流速、压力、递送的空气温度、环境温度、递送的空气湿度、环境湿度、环境音频信号、经由导管或导管内的空气传递的音频信号等数据。在一些情况下，附加传感器数据可以包括由用户接口和/或导管中的传感器收集的数据。在一些情况下，来自框1520的附加传感器数据与呼吸治疗系统的空气递送相关联。例如，在框1514处，可以使用与递送的空气温度相关联的附加传感器数据，以通过将递送的空气温度与围绕用户接口的密封的用户皮肤的温度进行比较来识别和/或确认无意空气泄漏。In some cases, additional sensor data may be received from the respiratory device at block 1520 and used to identify the characteristic at block 1514. Additional sensor data from the respiratory therapy device may include data acquired from a respiratory therapy system, such as the respiratory therapy system of FIG. 1 . Such additional sensor data may include data such as flow rate, pressure, delivered air temperature, ambient temperature, delivered air humidity, ambient humidity, ambient audio signals, audio signals transmitted via the duct or air within the duct, and the like. In some cases, additional sensor data may include data collected by sensors in the user interface and/or catheter. In some cases, additional sensor data from block 1520 is associated with air delivery by the respiratory therapy system. For example, at block 1514, additional sensor data associated with the delivered air temperature may be used to identify and/or confirm inadvertent air leakage by comparing the delivered air temperature to the temperature of the user's skin surrounding the seal of the user interface .
然而，在一些情况下，来自框1520的附加传感器数据可与用户接口的当前适配性相关联。在一个实例中，呼吸治疗系统可以包括能够检测关于用户面部或用户接口的信息的一个或多个传感器。例如，呼吸治疗装置中的RF传感器能够检测与用户接口在用户上的当前适配性相关联的测距信息。在另一实例中，一个或多个光学传感器(例如，可见光相机、无源红外传感器和/或有源红外传感器)可用于检测关于用户面部和/或用户接口的信息。However, in some cases, additional sensor data from block 1520 may be associated with the current suitability of the user interface. In one example, a respiratory therapy system may include one or more sensors capable of detecting information about a user's face or user interface. For example, an RF sensor in a respiratory therapy device can detect ranging information associated with the current fit of the user interface on the user. In another example, one or more optical sensors (eg, visible light cameras, passive infrared sensors, and/or active infrared sensors) may be used to detect information about the user's face and/or the user interface.
在一些情况下，可以在框1522处接收历史数据，并在框1514处将该历史数据用于识别特性。历史数据可包括历史传感器数据(例如，在框1502的先前例子处收集或接收的传感器数据)、历史特性数据(例如，与在框1514的先前例子处识别的特性相关联的信息)和/或其他历史数据(例如，先前适配性得分)。在框1518处，在框1514处识别特性可以包括将在框1522处接收的历史数据与在框1502处接收的传感器数据进行比较。例如，在框1522处接收历史数据可以包括在佩戴用户接口之前访问含有用户面部的热映射的存储器。在这种实例中，在框1518处，可以将该热映射与用户面部的当前热映射进行比较，该当前热映射可能是在用户佩戴用户接口时和/或在用户已经移除用户接口之后取得的。在两个热映射中检测到的差异可以用于识别特性(例如，意外的局部温度和/或无意空气泄漏)。In some cases, historical data may be received at block 1522 and used at block 1514 to identify characteristics. Historical data may include historical sensor data (eg, sensor data collected or received at a previous instance of block 1502), historical characteristic data (eg, information associated with a characteristic identified at a previous instance of block 1514), and/or Other historical data (e.g., previous fitness scores). At block 1518 , identifying the characteristics at block 1514 may include comparing the historical data received at block 1522 with the sensor data received at block 1502 . For example, receiving historical data at block 1522 may include accessing memory containing a heat map of the user's face prior to wearing the user interface. In such an example, at block 1518, the heat map may be compared to a current heat map of the user's face, which may have been obtained while the user was wearing the user interface and/or after the user has removed the user interface. of. The differences detected in the two heat maps can be used to identify characteristics (e.g., unexpected local temperatures and/or unintentional air leaks).
在另一实例中，在框1522处接收历史数据可包括访问含有与特定用户接口的密封相关联的先前轮廓回弹时间的存储器。在这种实例中，可以将先前轮廓回弹时间与针对用户接口的密封的相同部分新获取的轮廓回弹时间进行比较。这种比较可以指示密封随时间的劣化，密封随时间的劣化可导致不良适配性并且密封随时间的劣化不可避免地引发密封失败。因此，这种劣化可被检测为特性并用于通知用户替换密封。In another example, receiving historical data at block 1522 may include accessing memory containing previous contour rebound times associated with seals of a particular user interface. In such an instance, the previous profile springback time may be compared to a newly acquired profile springback time for the same portion of the seal of the user interface. This comparison can be indicative of seal degradation over time, which can lead to poor fit and which inevitably leads to seal failure. Therefore, this degradation can be detected as a characteristic and used to notify the user to replace the seal.
在一些情况下，可以使用机器学习算法来促进或实现识别特性。这种机器学习算法可以使用传感器数据的训练集合来训练，该传感器数据的训练集合已经由佩戴用户接口或以其他方式参与用户接口瞬态事件的一个或多个用户收集。训练数据可以包括关于经确定存在的特性的信息，尽管不必总是这种情况。在一些情况下，训练数据可包括关于用户接口的适配性的质量的信息。这种适配性信息质量可以基于用户的主观评估、使用其他装备(例如，实验室传感器和装备，诸如配备有专用传感器和/或专用感测装备的用户接口)收集的客观值等。在一些情况下，在框1514处识别的特性是该机器学习算法使用的特征。In some cases, machine learning algorithms may be used to facilitate or enable identification properties. Such machine learning algorithms may be trained using a training set of sensor data that has been collected by one or more users wearing the user interface or otherwise participating in transient events of the user interface. The training data may include information about characteristics determined to exist, although this need not always be the case. In some cases, the training data may include information about the quality of the user interface's suitability. This fitness information quality may be based on the user's subjective assessment, objective values collected using other equipment (eg, laboratory sensors and equipment, such as user interfaces equipped with specialized sensors and/or specialized sensing equipment), and the like. In some cases, the features identified at block 1514 are features used by the machine learning algorithm.
在一些情况下，识别与当前适配性相关联的特性可包括确定给定用户面部(例如，来自框1510的面部映射)和给定用户接口(例如，来自框1512的用户接口映射或其他用户接口识别信息)的预测的适配性的质量。在此类情况下，可以将用户面部的面部映射应用于给定用户接口的设计参数，以确定预测的适配性的质量(例如，该特定用户接口在该用户面部上的最佳可能适配性)。如果预测的适配性的质量低于阈值，则可以确定给定用户接口不适合用户使用。预测的适配性的质量还可用于确定当前适配性的给定评估(例如，如参考框1528描述的评估)是否可被改善(例如，当前适配性的改善是否可实现或可能发生)。例如，如果特定用户面部上的给定用户接口的预测的适配性的质量是“良好”(例如，从“不良”、“不错的”，“良好”和“非常良好”中，尽管可以使用用于表示适配性的质量的其他度量)，并且当前适配性被评估为“良好”，则可以确定在不改变用户接口的情况下可能没有适配性的质量的进一步改善。在另一实例中，如果预测的适配性的质量是“非常良好”并且当前适配性被评估为“不错的”，则可以确定调整其他因素(例如，除了改变用户接口之外)可以改善当前适配性，诸如修剪面部毛发、去除化妆品、改变床上位置或其他变化。In some cases, identifying characteristics associated with current suitability may include determining a given user's face (e.g., face mapping from block 1510) and a given user interface (e.g., a user interface mapping from block 1512 or other user The quality of the predicted suitability of the interface identification information). In such cases, facial mapping of the user's face can be applied to the design parameters of a given user interface to determine the quality of the predicted fit (e.g., the best possible fit of that particular user interface on that user's face sex). If the quality of the predicted suitability is below the threshold, it may be determined that the given user interface is not suitable for use by the user. The quality of predicted fitness may also be used to determine whether a given assessment of current fitness (eg, an assessment as described with reference to block 1528) can be improved (eg, whether improvements in current fitness are achievable or likely to occur) . For example, if the quality of the predicted fit of a given user interface on a specific user's face is "good" (e.g., from "bad", "good", "good" and "very good"), although one can use Other measures used to represent the quality of suitability), and the current suitability is evaluated as "good", it can be determined that there may be no further improvement in the quality of suitability without changing the user interface. In another example, if the quality of the predicted fit is "very good" and the current fit is evaluated as "good," it may be determined that adjusting other factors (eg, in addition to changing the user interface) may improve Current fit, such as trimming facial hair, removing makeup, changing position in bed, or other changes.
在框1524处，可以基于来自框1514的识别的特性并且可选地基于特性位置(例如，相对于面部映射和/或用户接口映射的位置)生成输出反馈。在框1524处生成输出反馈可以包括诸如经由GUI、扬声器、触觉反馈装置等来呈现该输出反馈。在一些情况下，输出反馈可呈现为用户图像上的叠加，诸如以增强现实叠加的形式。例如，图标、高亮显示、文本和其他标记可以叠加在用户的图像(例如，实况或非实况)上，以提供关于当前适配性的质量的反馈和/或用于如何改善当前适配性的指令。At block 1524, output feedback may be generated based on the identified characteristics from block 1514 and optionally based on the location of the characteristics (eg, relative to the facial map and/or user interface map). Generating output feedback at block 1524 may include presenting the output feedback, such as via a GUI, a speaker, a tactile feedback device, or the like. In some cases, the output feedback may be presented as an overlay on the user's image, such as in the form of an augmented reality overlay. For example, icons, highlights, text, and other markers may be overlaid on the user's image (e.g., live or non-live) to provide feedback on the quality of the current fit and/or on how to improve the current fit. instructions.
在一些情况下，输出反馈可包括已被识别的一个或多个特性并且可选地包括位置信息。例如，输出反馈可以是用户面部的图像或表示(例如，从可见光谱相机、热成像器取得的，或从面部映射以图形方式生成的)，该图像或表示叠加有指示检测到的特性的存在的图形或文本。在一个实例中，检测到的无意空气泄漏可以在检测到的无意空气泄漏的位置处通过箭头、突出显示的圆圈或其他引起注意力的视觉元素在用户面部的图像或表示上指示。In some cases, output feedback may include one or more characteristics that have been identified and optionally location information. For example, the output feedback may be an image or representation of the user's face (e.g., taken from a visible spectrum camera, a thermal imager, or graphically generated from a facial map) superimposed with an indicator indicating the presence of the detected feature graphics or text. In one example, a detected unintentional air leak may be indicated on an image or representation of the user's face by an arrow, highlighted circle, or other attention-grabbing visual element at the location of the detected unintentional air leak.
在一些情况下，在框1524生成输出反馈可以包括在框1526处确定并呈现建议的动作以改善适配性。确定并呈现建议的动作以改善适配性可以包括使用识别的特性及其位置信息来选择被设计为改善适配性的动作，然后呈现该动作(例如，经由文本、图形、音频反馈、触觉反馈等)。在一些情况下，可以基于查找表或算法来识别改善适配性的动作，该查找表或算法可以基于识别的特性(可选地包括其位置信息)来选择要采取的动作。例如，无意空气泄漏的检测可以与调整用户接口的条带的建议的动作关联，在这种情况下，无意空气泄漏的位置可以用于确定要调整哪个条带。In some cases, generating output feedback at block 1524 may include determining and presenting recommended actions at block 1526 to improve fitness. Determining and presenting suggested actions to improve fit may include using the identified characteristics and their location information to select an action designed to improve fit and then presenting the action (e.g., via text, graphics, audio feedback, tactile feedback wait). In some cases, actions to improve fitness may be identified based on a lookup table or algorithm that may select an action to take based on the identified characteristics, optionally including their location information. For example, detection of unintentional air leakage may be associated with a suggested action to adjust a strip of the user interface, in which case the location of the unintentional air leakage may be used to determine which strip to adjust.
然而，在一些情况下，确定要采取的动作可以基于机器学习算法。这种机器学习算法可以使用要采取的动作的训练集合以及采取动作之前和/或之后的适配性信息质量来训练。这种适配性信息质量可以基于用户的主观评估、使用其他装备(例如，实验室传感器和装备，诸如配备有专用传感器和/或专用感测装备的用户接口)收集的客观值等。在一些情况下，在框1514处识别的特性是该机器学习算法使用的特征。However, in some cases, determining the action to take can be based on machine learning algorithms. Such machine learning algorithms can be trained using a training set of actions to be taken and the quality of fitness information before and/or after taking the action. This fitness information quality may be based on the user's subjective assessment, objective values collected using other equipment (eg, laboratory sensors and equipment, such as user interfaces equipped with specialized sensors and/or specialized sensing equipment), and the like. In some cases, the features identified at block 1514 are features used by the machine learning algorithm.
在一些情况下，在框1524处生成输出反馈可以包括在框1526处生成当前适配性的评估。在框1526处生成当前适配性的评估可以包括使用传感器数据、识别的特性和/或特性位置信息。评估可以是数值得分(例如，适配性得分，诸如0至100之间的数值得分)、分类得分(例如，文本得分，诸如“良好”、“普通”和“不良”；颜色得分，诸如绿色、黄色和红色；或图形得分，诸如描绘无空气泄漏的密封、描绘小的空气泄漏的密封和描绘大的空气泄漏的密封)。In some cases, generating output feedback at block 1524 may include generating an assessment of current fitness at block 1526 . Generating an estimate of current suitability at block 1526 may include using sensor data, identified features, and/or feature location information. The evaluation may be a numerical score (e.g., a suitability score, such as a numerical score between 0 and 100), a categorical score (e.g., a text score, such as "good", "average", and "bad"; a color score, such as green , yellow and red; or graphical scores such as seals depicting no air leakage, seals depicting small air leakage, and seals depicting large air leakage).
在一些情况下，生成评估可以包括基于使用传感器数据、识别的特性和/或特性位置信息作为输入的等式算法生成评估。例如，适配性得分可以是与不同的识别的特性(例如，温度差异的量、温度差异距检测到的用户接口密封边缘的距离、检测到的音频信号中的无意泄漏的持续时间等)相关联的值的加权计算。In some cases, generating the estimate may include generating the estimate based on an equational algorithm using sensor data, identified features, and/or feature location information as inputs. For example, the fit score may be related to different identified characteristics (e.g., the amount of temperature difference, the distance of the temperature difference from the detected user interface sealing edge, the duration of detected inadvertent leakage in the audio signal, etc.) Weighted calculation of associated values.
在一些情况下，生成评估可以至少部分地基于与历史数据(例如，在框1522处接收的历史数据)的比较。在此类情况下，该评估可以至少部分地基于与识别的一个或多个特性相关联的值是否被示出为改善或降级，在这种情况下，改善可以保证适配性得分从先前适配性得分开始增加，并且降级可以保证适配性得分从先前适配性得分开始减少。In some cases, generating the estimate may be based at least in part on a comparison with historical data (eg, historical data received at block 1522). In such cases, the evaluation may be based at least in part on whether the value associated with the identified one or more characteristics is shown to be improved or degraded, in which case the improvement may ensure that the fitness score improves from the previous fit. The fitness score starts to increase, and downgrading ensures that the fitness score starts to decrease from the previous fitness score.
在一些情况下，生成评估可以基于机器学习算法。这种机器学习算法可以使用传感器数据、识别的特性和/或特性位置信息的训练集合来训练。在一些情况下，训练集合可以包括适配性信息质量。这种适配性信息质量可以基于用户的主观评估、使用其他装备(例如，实验室传感器和装备，诸如配备有专用传感器和/或专用感测装备的用户接口)收集的客观值等。在一些情况下，在框1514处识别的特性是该机器学习算法使用的特征。In some cases, the generated evaluation can be based on machine learning algorithms. This machine learning algorithm can be trained using a training set of sensor data, identified features, and/or feature location information. In some cases, the training set may include adaptive information quality. This fitness information quality may be based on the user's subjective assessment, objective values collected using other equipment (eg, laboratory sensors and equipment, such as user interfaces equipped with specialized sensors and/or specialized sensing equipment), and the like. In some cases, the features identified at block 1514 are features used by the machine learning algorithm.
虽然过程1500在本文中被示出和描述为以特定顺序发生，但是更一般地，过程1500的各个框可以以任何合适的顺序执行，并且具有更少和/或附加框。例如，在一些情况下，不使用框1520、框1522、框1512和框1518。Although process 1500 is shown and described herein as occurring in a specific order, more generally, the various blocks of process 1500 may be performed in any suitable order and with fewer and/or additional blocks. For example, in some cases, block 1520, block 1522, block 1512, and block 1518 are not used.
图9至图10和图14至图15中的流程图表示用于收集和分析数据以选择用于呼吸压力治疗的最佳接口并进行跟进分析(诸如选择的用户接口的适配性)的示例机器可读指令。在该实例中，机器可读指令包括由以下执行的算法：(a)处理器；(b)控制器；和/或(c)一个或多个其他合适的处理装置。该算法可以由存储在有形介质上的软件来体现，该有形介质为诸如闪存、CD-ROM、软盘、硬盘驱动器、数字视频(通用)盘(DVD)，或其他存储装置。然而，本领域普通技术人员将容易理解，整个算法和/或其部分可以替代地由除处理器之外的装置来执行和/或以公知的方式体现在固件或专用硬件中(例如，该整个算法和/或其部分可以由专用集成电路[ASIC]、可编程逻辑装置[PLD]、现场可编程逻辑装置[FPLD]、现场可编程门阵列[FPGA]、离散逻辑等来实施)。例如，接口的任何或全部部件可以由软件、硬件和/或固件来实施。此外，可以手动实施由流程图表示的一些或全部机器可读指令。此外，尽管参考图9至图10和图14至图15中绘示的流程图描述了示例算法，但是本领域普通技术人员将容易理解，可以替代地使用实施示例机器可读指令的许多其他方法。例如，可以改变框的执行顺序，和/或可以改变、消除或组合描述的框中的一些。The flowcharts in Figures 9-10 and 14-15 represent the methods used to collect and analyze data to select the best interface for respiratory pressure therapy and perform subsequent analysis, such as the suitability of the selected user interface. Example machine-readable instructions. In this example, the machine-readable instructions include algorithms executed by: (a) a processor; (b) a controller; and/or (c) one or more other suitable processing devices. The algorithm may be embodied by software stored on a tangible medium such as flash memory, CD-ROM, floppy disk, hard drive, digital video (versatile) disk (DVD), or other storage device. However, one of ordinary skill in the art will readily appreciate that the entire algorithm and/or portions thereof may alternatively be executed by means other than a processor and/or be embodied in firmware or dedicated hardware in a well-known manner (e.g., the entire algorithm The algorithm and/or portions thereof may be implemented by an application specific integrated circuit [ASIC], a programmable logic device [PLD], a field programmable logic device [FPLD], a field programmable gate array [FPGA], discrete logic, etc.). For example, any or all components of the interface may be implemented in software, hardware, and/or firmware. Additionally, some or all of the machine-readable instructions represented by the flowcharts may be implemented manually. Furthermore, although the example algorithms are described with reference to the flowcharts illustrated in FIGS. 9-10 and 14-15 , those of ordinary skill in the art will readily appreciate that many other methods of implementing the example machine-readable instructions may alternatively be used . For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined.
如本申请所用，术语“部件”、“模块”、“系统”等一般是指计算机相关实体，或者是硬件(例如，电路)、硬件和软件的组合、软件，或者是与具有一个或多个特定功能的操作机器有关的实体。例如，部件可以是但不限于：在处理器(例如，数字信号处理器)上运行的过程、处理器、对象、可执行程序、执行线程、程序和/或计算机。作为说明，在控制器上运行的应用程序以及控制器均可以是部件。一个或多个部件可以驻留在过程和/或执行线程内，并且部件可以局部化于一个计算机上和/或分布在两个或更多个计算机之间。此外，“装置”可以以以下形式出现：特别设计的硬件；通过在其上执行使该硬件能够执行特定功能的软件而专用化的通用硬件；存储在计算机可读介质上的软件；或其组合。As used in this application, the terms "component," "module," "system" and the like generally refer to a computer-related entity, either hardware (e.g., circuitry), a combination of hardware and software, software, or an entity having one or more An entity related to operating a machine for a specific function. For example, a component may be, but is not limited to, a process, processor, object, executable program, thread of execution, program and/or computer running on a processor (eg, a digital signal processor). As an illustration, both the application running on the controller and the controller can be components. One or more components may reside within a process and/or thread of execution, and a component may be localized on one computer and/or distributed between two or more computers. Additionally, a "device" may take the form of: specially designed hardware; general-purpose hardware specialized by executing software thereon that enables the hardware to perform specific functions; software stored on a computer-readable medium; or a combination thereof .
本文使用的术语仅用于描述特定实施例的目的，并不旨在限制本发明。如本文所用，单数形式“一个”、“一种”和“该”也旨在包括复数形式，除非上下文另有清楚指示。此外，就在详细说明书和/或权利要求中使用的术语“包括(including)”、“包括(includes)”、“具有(having)”、“具有(has)”、“有”或其变体而言，此类术语旨在以类似于术语“包括(comprising)”的方式是包括性的。The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, as used in the detailed description and/or claims, the terms "including", "includes", "having", "has", "have" or variations thereof , such terms are intended to be inclusive in a manner similar to the term "comprising."
除非另有定义，否则本文使用的全部术语(包括技术和科学术语)具有与本领域普通技术人员通常理解的相同含义。此外，诸如在常用词典中定义的那些术语应当被解释为具有与它们在相关技术的上下文中的含义一致的含义，并且将不以理想化或过于正式的意义来解释，除非本文明确地如此定义。Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. Furthermore, terms such as those defined in commonly used dictionaries should be construed to have meanings consistent with their meaning in the context of the relevant technology and will not be construed in an idealized or overly formal sense unless expressly so defined herein. .
来自以下权利要求1至100中任一项的一个或多个的一个或多个要素或方面或步骤，或其任意部分可以与来自其他权利要求1至100中任一项的一个或多个的一个或多个要素或方面或步骤，或其任意部分，或者其组合进行组合，以形成本公开的一个或多个附加实施方式和/或权利要求。One or more elements or aspects or steps from one or more of the following claims 1 to 100, or any part thereof, may be combined with one or more elements or aspects or steps from any one of the other claims 1 to 100 One or more elements or aspects or steps, or any portion thereof, or combinations thereof are combined to form one or more additional embodiments and/or claims of the present disclosure.
虽然上面已经描述了本发明的各种实施例，但是应当理解，这些实施例仅是作为实例而非限制来呈现的。尽管已经参考一个或多个实施方式说明和描述了本发明，但是在阅读和理解本说明书和附图之后，本领域的其他技术人员将会想到或知晓等同的替代和修改。此外，虽然本发明的特定特征可能仅相对于数个实施方式中的一个进行了公开，但这种特征可以与其他实施方式的一个或多个其他特征组合，这对于任何给定或特定应用可能是期望且有利的。因此，本发明的广度和范围不应受到上述实施例中的任一个的限制。相反，本发明的范围应当根据以下权利要求及其等同物来限定。While various embodiments of the present invention have been described above, it should be understood that these embodiments are presented by way of example only and not limitation. Although the invention has been illustrated and described with reference to one or more embodiments, equivalent alternatives and modifications will occur to others skilled in the art upon reading and understanding this specification and the accompanying drawings. Furthermore, while a particular feature of the invention may be disclosed with respect to only one of several embodiments, such feature may be combined with one or more other features of other embodiments, as may be desirable for any given or particular application. is expected and beneficial. Accordingly, the breadth and scope of the present invention should not be limited by any of the above-described embodiments. Rather, the scope of the invention should be defined in accordance with the following claims and their equivalents.
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